About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We're hiring a Product Operations Manager — Feedback Loops to own and continuously improve how customer signal flows into product and research decisions at Anthropic. This is a horizontal, org-wide role — you won't be embedded in a single product team, you'll build the shared operating system for voice of the customer that every product team, every surface, and every GTM motion plugs into. Feedback at Anthropic is uniquely high-leverage. We're building on frontier models that evolve constantly, serving customers from individual developers to the largest enterprises, across multiple surfaces (API, claude.ai , Claude Code). Customer signal arrives from everywhere — field conversations, support interactions, early access programs, in-product telemetry — and the opportunity is to make that signal a first-class, structured input to every product and research decision. This role will build the system that makes customer voice as easy to act on as any other data source. You treat feedback loops as a product. You're obsessed with making it effortless for the field to share what they're hearing and for product teams to know what matters most. You build AI-enabled systems that do the first pass so humans can focus on judgment, not triage. You think like a product manager, not a process administrator. Your work will directly impact how fast Anthropic learns from its customers and how reliably that learning shapes what we build next. Key Responsibilities You'll own the operating system for customer feedback across all of Anthropic — one shared platform, not a collection of per-team processes. Working horizontally across every Product team, Research PM, GTM, Customer Success, and Support, you'll establish the intake, synthesis, and routing infrastructure that makes voice of the customer a first-class input to every roadmap. You'll drive adoption through influence, making it so obviously useful that teams pull from it rather than get pushed to it. Feedback Intake & System of Record - Own the single, org-wide pipeline that captures customer feedback from every channel — field teams, support, early access programs, in-product signals — into one structured system of record that serves every product surface. - Build intake workflows that meet teams where they already work (Slack, Gong, CRM) without creating a documentation tax. Obsess over the submitter experience so that sharing feedback is faster than not sharing it. AI-Enabled Synthesis & Triage - Build Claude-powered pipelines that enrich, tag, cluster, and summarize unstructured feedback into trackable issues — doing the first-pass work so humans focus on verification and judgment. - Design the human-in-the-loop model: Claude proposes, PMs and field teams correct, and the system learns from those corrections over time. - Partner with Engineering and Research on tooling strategy, evals, and the closed-loop data that makes synthesis quality measurably improve. Routing & Closing the Loop - Establish clear routing so the right feedback reaches the right product or research owner at the right time — including the path from product signal back into model training priorities. - Build the visibility layer that gives GTM and Support a clear line of sight from customer input to roadmap outcome, so they can close the loop with customers confidently and in real time. Voice of the Customer Programs - Partner deeply with GTM, Customer Success, and Sales to design and run structured voice of the customer programs — customer advisory boards, early access programs, design partner cohorts — that generate high-signal feedback by design. - Define what "high-signal" means: feedback tied to specific use cases, blocker severity, revenue context, and customer segments so product teams can make confident tradeoffs. Continuous Improvement - Define and track success metrics for feedback loop health — time-to-triage, signal quality, roadmap influence, field satisfaction — and use them to identify bottlenecks. - Run regular retros with Product and GTM partners and feed learnings back into process and tooling improvements. Scale what works through documentation and enablement. You may be a good fit if you: - Have 7+ years in product operations, customer insights, voice of the customer programs, or related roles in fast-paced tech companies. - Have personally shipped AI-enabled processes and systems — you've written the prompts, built the evals, and iterated on production LLM workflows yourself. You can talk about model behavior with specificity, not just direct others to build. - Have owned a customer feedback program end-to-end — intake, synthesis, routing, and closing the loop — that product teams actually used to make decisions. The customer mix can be enterprise, PLG, design partner, or dev community; what matters is that you designed it and ran it. - Have operated at earlier-stage and scaling companies (Series B-D or equivalent) where you built things that didn't exist yet, shipped v1s in weeks not quarters, and iterated in public. - Have operated in horizontal, cross-org roles before — you know how to build shared infrastructure that many teams depend on, drive adoption through influence rather than mandate, and earn trust across functions that don't report to you. - Are comfortable with ambiguity and can create structure where none exists — you've built the v1 of a system and iterated it into something teams rely on. - Are service-oriented and obsessed with making it easy for others to do great work. Strong candidates may also have experience with: - Building AI-native workflows end-to-end — prompt design, evals, closed-loop improvement — and pushing the boundaries of what automation can own. - Product Management, Customer Success Operations, or Research Operations. - Feedback tooling ecosystems (Productboard, Dovetail, or homegrown equivalents) and the tradeoffs between buy vs. build. - Treating process as a product with users, metrics, and continuous iteration. - Track record of building and scaling operations programs from zero to one. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $260,000 - $325,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicApr 12, 2026

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⚡

People Research Scientist, Recruiting

Negotiable

👤 HumanFull-time

By AnthropicJun 15, 2026

By AnthropicMar 20, 2026

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⚡

Head of GovTech Sales

Negotiable

👤 HumanFull-time

By AnthropicMar 31, 2026

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⚡

Head of Consolidations & Intercompany

Negotiable

👤 HumanFull-time

By AnthropicMay 27, 2026

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⚡

G&A Compensation Partner

Negotiable

👤 HumanFull-time

By AnthropicJun 25, 2026

↗

⚡

Field Marketing Lead, EMEA

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking a Field Marketing Lead to build and scale our field marketing and demand generation capabilities across EMEA. As a founding member of our EMEA field marketing function, you'll establish the programs and infrastructure that drive pipeline and revenue growth across diverse European markets, while supporting our mission of ensuring safe and beneficial AI development. This role requires a sophisticated understanding of B2B marketing with demonstrated success in field marketing and working account-based marketing teams to create a regional growth engine. You'll develop and execute comprehensive strategies that drive revenue growth in partnership with Sales, Segment Marketing, Product Marketing teams, creating compelling programs and flywheel motions that empower the EMEA Sales team to achieve their revenue targets. EMEA represents both our biggest international opportunity and our most complex challenge—a region where data sovereignty requirements, diverse regulatory frameworks, and sophisticated local competitors demand a fundamentally different approach than what's worked in North America. You'll work closely with EMEA sales leadership, the global field marketing team, and cross-functional partners to ensure programs directly support revenue growth and strategic account advancement. Responsibilities - Build and lead the EMEA field marketing function, establishing scalable frameworks and processes from scratch in the region - Drive field marketing initiatives across enterprise, while building scaled programs for startups, adapting strategies for diverse European markets and buying behaviors - Create and implement field marketing programs including executive roundtables, customer events, industry conferences, partner programs, and ABM activations - Partner closely with EMEA sales leadership to align field marketing programs with territory and account-specific goals that directly achieve pipeline and revenue goals - Establish measurement frameworks including lead scoring, attribution models, and ROI reporting to demonstrate marketing's impact on revenue - Evaluate and select premium third-party events that align with business goals and create high-impact activation strategies - Collaborate with global Field Marketing and Segment Marketing teams to ensure EMEA programs align with company-wide strategy while meeting local market needs - Coordinate with EMEA Solutions Marketing and Product Marketing to ensure consistent messaging and positioning in all regional programs - Manage regional resources including building relationships with key partners, vendors, and industry organizations across EMEA - Build and manage a regional field marketing budget with strong financial discipline and ROI focus - Drive continuous improvement through post-program analysis, stakeholder feedback, and data-driven optimization You may be a good fit if you - Have 10+ years of B2B enterprise marketing experience with blended expertise in field marketing, account-based marketing, demand generation in EMEA markets - Demonstrate deep understanding of B2B enterprise sales cycles and buying processes - experience working within software companies is required for this position - Have a track record of successfully building and scaling field marketing and demand generation programs from the ground up - Have strong analytical skills and data-driven approach to program optimization and attribution - Have demonstrated success in contributing to significant revenue goals through integrated marketing initiatives - Possess international marketing experience and understanding of regional market dynamics across European markets - Are a proven self-starter who can build and run sophisticated programs with small teams in fast-paced startup environments - Have strong project management skills with experience managing complex, multi-country programs simultaneously - Possess exceptional budgeting and financial management capabilities with experience managing substantial field marketing budgets - Demonstrate cultural awareness and ability to adapt strategies for diverse European markets - Excel at cross-functional collaboration, particularly with sales teams and executive stakeholders - Are comfortable with ambiguity and thrive in fast-paced, evolving environments with a bias for thoughtful action Strong candidates may also - Have experience marketing AI/ML or complex technical products to enterprise customers - Have experience building and leading demand generation teams in EMEA - Have knowledge of account-based marketing (ABM) strategies and execution - Have experience at high-growth technology companies such as Okta, Splunk, Snowflake, or Workday - Have previous experience as a first field marketing hire in a new region - Have fluency in multiple European languages - Have understanding of EMEA regulatory and compliance requirements for marketing activities - Have experience evaluating and activating at premium third-party events strategically, including hospitality management at high-end venues and cultural experiences Travel requirements Role-specific policy: For this role, we expect all staff to be able to work from our London office at least 2 days a week. We encourage you to apply even if you might need some flexibility for an interim period of time for relocation. This role also requires approximately 40-50% travel within EMEA for field programs, customer engagements, events, and stakeholder meetings, with additional travel to Anthropic offices for alignment and planning sessions. Deadline to apply: None. Applications will be reviewed on a rolling basis, starting in the new year. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £160,000 - £200,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicDec 11, 2025

By AnthropicOct 19, 2025

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Anthropic Fellows Program, The Anthropic Institute (Economics & Policy)

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Apply using this link . We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you. This page is specific to one of the Anthropic Fellows Workstreams; see also the main Anthropic Fellows posting . Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond. What to expect - 4 months of full-time research - Direct mentorship from Anthropic researchers - Access to a shared workspace (in either Berkeley, California or London, UK) - Connection to the broader AI safety and security research community - Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) - Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension). Fellows workstreams Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams. Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application . You can see an overview of the current workstreams below: - AI Safety Fellows - AI Security Fellows - ML Systems & Performance Fellows - Reinforcement Learning Fellows - Economics & Societal Impacts Fellows Across the workstreams, you may be a good fit if you: - Are motivated by making sure AI is safe and beneficial for society as a whole - Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic - Have a strong technical background in computer science, mathematics, or physics - Thrive in fast-paced, collaborative environments - Can implement ideas quickly and communicate clearly Strong candidates may also have: - Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity) - Experience in areas of research or engineering related to their workstream Candidates must be: - Fluent in Python programming - Available to work full-time on the Fellows program The Anthropic Institute Fellows (Economics & Policy) Mentors, research areas, & past projects Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include: - Economics - Maxim Massenkoff - Peter McCrory - Policy, Security, and Society - Jack Clark - Marina Favaro - Jim Baker Projects in this workstream may include: - Designing and conducting empirical research on AI's economic effects, drawing on external data sources - Developing new methodological approaches for studying AI's impact on labor markets, the future of work, and society - Analysing the offense–defense balance for AI-enabled cyber and bio capabilities as models scale - Measuring the extent to which model performance increases with custom harnesses? - Identifying market driven mechanisms that could improve societal resilience to anticipated threats from AI systems? - Identifying which metrics relating to AI R&D could service as early warning signals for recursive self-improvement For past project examples, see: - How AI Impacts Skill Formation : Judy Shen and Alex Tamkin - Stress-Testing Model Specs Reveals Character Differences among Language Models : Jifan Zhang, Henry Sleight, Andi Peng, John Schulman, and Esin Durmus Unique candidate criteria You might be a particularly great fit for this workstream if you: - Have an interest in economics or policy research; prior experience in this area is a plus but not required - Are adaptable and collaborative, able to take direction and contribute to team priorities rather than needing to pursue a predetermined research agenda - Are skilled at writing up and communicating your results, even when they're null or unexpected - Are passionate about translating research insights into actionable recommendations for improving AI systems and informing policy Logistics Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada . We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program. Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada. Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis. Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations. Applications and interviews are managed by Constellation , our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds. Apply here The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program. Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicApr 24, 2026

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⚡

Transaction Principal

Negotiable

Negotiable

👤 HumanFull-time

By AnthropicJan 17, 2025

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⚡

Engineering Manager, Safeguards Review Tooling

Negotiable

👤 HumanFull-time

By AnthropicJun 10, 2026

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⚡

Engineering Manager, Cybersecurity Products

Negotiable

👤 HumanFull-time

By AnthropicMay 30, 2026

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⚡

Data Scientist, Safeguards

Negotiable

👤 HumanFull-time

By AnthropicJun 2, 2026

By AnthropicJun 10, 2026

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⚡

Anthropic Fellows Program, Reinforcement Learning

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Apply using this link . We are accepting applications on a rolling basis for the next cohort of Anthropic Fellows, which is expected to start in late September. In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the September start date doesn't work for you. This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting . Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond. What to expect - 4 months of full-time research - Direct mentorship from Anthropic researchers - Access to a shared workspace (in either Berkeley, California or London, UK) - Connection to the broader AI safety and security research community - Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) - Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension). Fellows workstreams Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams. Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application . You can see an overview of the current workstreams below: - AI Safety Fellows - AI Security Fellows - ML Systems & Performance Fellows - Reinforcement Learning Fellows - Economics & Societal Impacts Fellows This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting . Across the workstreams, you may be a good fit if you: - Are motivated by making sure AI is safe and beneficial for society as a whole - Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic - Have a strong technical background in computer science, mathematics, or physics - Thrive in fast-paced, collaborative environments - Can implement ideas quickly and communicate clearly Strong candidates may also have: - Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity) - Experience in areas of research or engineering related to their workstream Candidates must be: - Fluent in Python programming - Available to work full-time on the Fellows program Reinforcement Learning Fellows Mentors, research areas, & past projects Fellows will undergo a project selection & mentor matching process. Potential research areas and mentors include: - Ruhua Jiang - Kaidi Cao - Sunny Duan - David Brandfonbrener - Colt Steele - Dino Distefano - Will Williams Projects in this workstream may include: - Building model-based tools to better understand AI training data and improve training data quality - A research project to better understand generalization - Creating RL environments to improve Claude models at capabilities that are within your domain of expertise - Building RL environments for safety-related tasks - Conducting research and implementing solutions in areas such as RL algorithms Unique candidate criteria You might be a particularly great fit for this workstream if you: - Have strong software engineering skills with experience building complex ML systems - Can balance research exploration with engineering rigor and operational reliability - Enjoy collaborating across research and engineering disciplines - Are comfortable working with large-scale distributed systems and high-performance computing - Have experience with training, fine-tuning, or evaluating large language models - Are adept at analyzing and debugging model training processes Logistics Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada . We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program. Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada. Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis. Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations. Applications and interviews are managed by Constellation , our recruiting partner. Clicking "Apply here" will take you to their portal, and updates will come from a Constellation address. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities focused projects in future rounds. Apply here The below are Anthropic's policies for full time roles. These do NOT apply to the Fellows Program. Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicApr 10, 2026

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TPU Kernel Engineer

Negotiable

👤 HumanFull-time

By AnthropicMay 22, 2025

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⚡

Technical Specialist, Claude Code

Negotiable

👤 HumanFull-time

By AnthropicJun 25, 2026

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⚡

Technical Program Manager, Safeguards (Infrastructure & Evals)

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Safeguards Engineering builds and operates the infrastructure that keeps Anthropic's AI systems safe in production — the classifiers, detection pipelines, evaluation platforms, and monitoring systems that sit between our models and the real world. That infrastructure needs to be not just correct, but reliable : when a safety-critical pipeline goes down or degrades, the consequences can be serious, and they can be invisible until someone looks closely. As a Technical Program Manager for Safeguards Infrastructure and Evals, you'll own the operational health and forward momentum of this stack. Your primary responsibility is driving reliability — owning the incident-response and post-mortem process, ensuring SLOs are defined and met in partnership with various teams, and making sure that when things go wrong, the right people know, the right actions get taken, and those actions actually get closed out. Alongside that ongoing operational rhythm, you'll coordinate the larger platform investments: migrations, eval-platform improvements, and the cross-team dependencies that connect them. This role sits at the intersection of operations and program management. It requires genuine technical depth — you need to understand how these systems work well enough to triage effectively, judge what's actually safety-critical versus what can wait, and have informed conversations with the engineers building and maintaining them. But the core of the job is keeping the machine running well and the work moving. What You'll Do: - Own the Safeguards Engineering ops review - Drive the recurring cadence that keeps the team informed and coordinated: surfacing recent incidents and failures, bringing visibility to reliability trends, and making sure the right people are in the room when decisions need to be made. This is the heartbeat of how Safeguards Eng stays ahead of operational risk. - Drive incident tracking and post-mortem execution - When incidents happen — and in this space, they happen regularly — you'll make sure they get followed through properly. That means tracking incidents across the organization (including those owned by partner teams like Inference), ensuring post-mortems get written, and most critically, making sure the action items that come out of them actually get done. Closing the loop on post-mortem actions is one of the highest-leverage things this role does. - Establish and maintain SLOs with partner teams - Work with Safeguards Engineering teams and key partners — particularly Inference and Cloud Inference — to define service-level objectives for safety-critical pipelines. Then build the tracking and reporting that makes it possible to tell whether those SLOs are being met, and surface it when they're not. - Maintain runbook quality and incident-ownership clarity - Safety-critical systems need clear playbooks for when things go wrong. Partner with engineering leads to keep runbooks accurate, actionable, and up to date — and ensure that ownership of incidents (including for areas like account-banning false positives and CSAM detection) is unambiguous so that nothing falls through the cracks during an active incident. - Drive platform migrations and infrastructure projects - Own the program management for the larger infrastructure work on the roadmap: migrating the infra from one platform to the next, moving from one incident platform to the next and from one cloud system monitoring to another, and other migrations as they come. These are cross-team efforts with real dependencies — your job is to keep them sequenced, on track, and connected to the teams that need them. - Coordinate evals platform improvements - Partner with the evals engineering team to drive improvements to the evaluation platform — including self-serve capabilities and the broader eval factory infrastructure. Help scope the work, track dependencies on other Safeguards systems, and make sure the evals platform is keeping pace with the team's needs. You might be a good fit if you: - Have solid technical program management experience, particularly in operational or infrastructure-heavy environments — you're comfortable owning a mix of ongoing operational cadences and discrete project work simultaneously. - Understand how production ML systems work well enough to triage incidents intelligently and have substantive conversations with engineers about what's going wrong and why — you don't need to write the code, but you need to follow the technical thread. - Are energized by closing loops. Post-mortem action items that never get done, SLOs that no one checks, runbooks that go stale — these things bother you, and you know how to build the processes and follow-ups that fix them. - Can work effectively across team boundaries — comfortable coordinating with partner teams (like Inference) where you don't have direct authority, and skilled at keeping shared work moving through influence and clear communication. - Thrive in environments where the work shifts between "keep the lights on" and "build something new" — and can context-switch between incident follow-ups and longer-horizon platform projects without dropping either. - Have experience with or strong interest in AI safety — you understand why the reliability of a safety-critical pipeline is a different kind of problem than the reliability of a product feature, and that distinction motivates you. Strong candidates may also: - Have experience with SRE practices, incident management frameworks, or on-call operations at scale. - Have worked on or with evaluation infrastructure for ML systems — understanding how evals get designed, run, and interpreted. - Have experience driving infrastructure migrations in complex, multi-team environments — particularly where the migration touches operational systems that can't go offline. - Be familiar with monitoring and alerting tooling (PagerDuty, Datadog, or equivalents) and the operational culture around them. Deadline to apply: None, applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $290,000 - $365,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicFeb 4, 2026

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Technical Program Manager, Compute

Negotiable

👤 HumanFull-time

By AnthropicMar 2, 2026

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⚡

Technical Cyber Threat Investigator

Negotiable

👤 HumanFull-time

By AnthropicJan 14, 2026

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Staff+ Software Engineer, Full-stack

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Product Engineering org is looking for experienced engineers with strong full-stack fundamentals to join one of teams owning our current or emergent products. You'll be a technical leader who thinks holistically about the consumer and/or enterprise end user experience - be that via Claude.ai , the Anthropic API, enterprise deployments, Claude Code, or mission-driven applications - and carry real end-to-end ownership. You'll partner with engineering managers, product leaders, designers, and researchers to understand new model capabilities and redefine what is possible for users in the world of LLMs - and how to build it. We’ll look to you to have a product-oriented mindset and input, own technical quality across the stack (performance, accessibility, reliability, and developer experience), scale your efforts to millions of users on a global scale, and carry genuine excitement about what AI makes possible. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. What you'll do: Developer Experience: You'll build the products and tools - console, SDKs, docs, and observability - that give developers the confidence to rely on Claude in their most critical applications. Our mission is to meet developers where they are and bring them closer to the ceiling of what's possible with our models and API. That means building trust through great platform fundamentals, inspiring developers to raise the bar in how they use Claude's capabilities, and accelerating the path to agentic development by designing for both human and AI developers. You'll work closely with teams across the Platform org to turn Claude's newest capabilities into experiences developers can actually pick up and run with - from first prompt to production agent. Beneficial Deployments: Beneficial Deployments Engineering brings Claude to organizations doing the most good with the fewest resources — nonprofits, schools, healthcare providers, researchers, and economic mobility programs.We're looking for a full-stack engineer to build the access programs, tooling, and product work that make frontier AI usable for teams that couldn't afford this capacity any other way. Vertical AI Products: Purpose-built experiences for specific industries where Claude can transform complex professional work. We're currently building for three verticals, with more to come: - Financial Services — analysts and bankers across investment banking, asset management, insurance, and corporate finance, building models, memos, and decks under deadline. We're building deeply integrated experiences inside the tools they already use — retrieval, analysis, and document generation that holds up to executive review. - Life Sciences — an agentic research platform for scientists: specialist agents for computational biology, literature review, and regulatory review, built on model capabilities we're investing in for biology and chemistry. Live with early customers and expanding fast. - Healthcare — spanning payer workflows like claims, prior authorization, and utilization management, as well as clinical applications. Work where accuracy isn't a feature, it's the whole product — and where compliance is part of the engineering. Enterprise AI Products: You'll work on the products that make Claude a daily-use tool for enterprise customers across industries – the connective tissue that lets Claude operate effectively across workflows. On this team you will systematically understand why Enterprise users aren't activating, what's blocking adoption, and building the capabilities to close those gaps.Some of our focuses are: - Extensibility — plugins, skills, connectors, and the MCP ecosystem that lets a company shape Claude around their specific workflows and distribute that work across teams. - Context — enterprise knowledge, organizational memory, and the retrieval layer that makes Claude genuinely aware of a company's people, documents, and workflows. A connected, contextual Claude is the difference between a general-purpose chatbot and a real coworker. - Proactivity — Cowork suggestions, workflow capture, ambient Claude inside the apps people already use. Moving from "Claude answers when asked" to "Claude notices what you need". Public Sector: Build products that deliver Claude to the U.S. federal & state governments and allied democracies — from FedRAMP environments to classified networks. We're a startup-minded team with huge surface area: we own Claude for Government, ship zero-to-one products into the most regulated environments in the world, and work directly with the agencies using them Enterprise Foundations: You'll build the systems large organizations require before they can adopt Claude at scale: identity and permissions, security and compliance controls, and the admin analytics that let them see how it's being used. This is the work that turns "we love the demo" into a signed enterprise deal.The role is part product, part platform. You'll work closely with Product and GTM to understand what our largest customers need, then build it once in a way that works across Claude.ai, Claude Code, and Cowork. Growth: Drive user acquisition, engagement, retention, and monetization through data-driven strategies and technical implementations. At Anthropic, we're not just building AI tools; we're reimagining how AI can enhance and expand its user base! As a member of the growth team, you will have a unique opportunity to shape our growth strategy. You will work with a cross-functional team of engineers, data scientists, marketers, and product managers to design, implement, and optimize growth initiatives that scale our AI-powered tools and maximize their impact. Marketplace: builds the platform that connects Claude-powered enterprise tools through technology partnerships and deeper customer relationships. We work closely with business development, sales, product, and GTM teams, creating the infrastructure that powers partner onboarding, customer storefronts, transaction and entitlement flows at scale. We're building the technical scaffolding for a new offering, tackling the challenges at the intersection of commercial motions, platform architecture, and partner integrations so that enterprises, platforms, and Anthropic can transact with confidence. Passport: We're building the identity and verification product layer that enables safe model launches as Claude's capabilities expand. This critical effort partners with Safeguards, Auth & Identity, Policy, and Product teams across API, Claude.ai , and third-party platforms as customers, creating the systems for KYC/KYB, trust grant issuance and inheritance, and end-user verification that flow across every Anthropic surface. We sit at the intersection of trust, compliance, and product velocity, delivering the verification primitives that let Anthropic ship advanced model capabilities to the right users at massive scale. You might be a good fit if you: - Have a minimum of 8 years of practical full-stack engineering experience, ideally with 2+ years operating at a Staff or equivalent technical leadership level - Have led the design and delivery of complex, consumer or B2B user-facing products across the full stack - Are a technical expert in modern frontend and backend development, with demonstrated depth in key languages and frameworks (ie. React, Typescript) - Take a product-focused approach to building solutions that are robust, scalable, and easy to use - Have worked in early start-up or otherwise fast moving, rapidly evolving environments, and have ideally built products from 0 to 1 Care deeply in investing in the mentorship and growth of your peers - Have successfully driven cross-team/cross-org organizational alignment to get impactful work shipped, and work with influence over authority - Have experience establishing engineering standards, component architectures, and development best practices - Thrive in fast-paced environments and can navigate ambiguity to deliver high-quality products Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, NJ, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicApr 8, 2026

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Solutions Architect, National Security

Negotiable

👤 HumanFull-time

By AnthropicFeb 20, 2026

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⚡

Software Engineer, Safeguards Infrastructure

Negotiable

👤 HumanFull-time

By AnthropicJan 21, 2026

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⚡

Applied AI Architect, Public Sector

By AnthropicMay 25, 2026

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Head of ANZ, Applied AI

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As the founding leader of Applied AI Solutions Architecture in ANZ, you will drive the adoption of frontier AI by enabling the deployment of Anthropic's products (Claude for Enterprise, Claude Code, and API) across Australian and New Zealand enterprises and digital-first organizations. You'll leverage your technical skills and consultative sales experience to drive positive AI transformation that addresses our customers' business needs, meets their technical requirements, and provides a high degree of reliability and safety. You'll be responsible for building and leading the ANZ Applied AI team from the ground up. Applied AI comprises Solutions Architects, Product Engineers, and Finetuning Engineers. You will establish processes and best practices for the region's technical pre-sales engagements based on your years of experience, help each team member achieve success, high productivity, and career growth, and represent Anthropic as a technical lead on some of its most important partnerships across Australia and New Zealand. In collaboration with the Sales, Product, and Engineering teams globally and locally, you'll help enterprise partners across ANZ incorporate leading-edge AI systems into their cutting-edge products and platforms. You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike. You will play a critical role in identifying opportunities to innovate and differentiate our AI systems, while maintaining our best-in-class safety standards. Responsibilities - Build and manage the foundational team of Applied AI professionals in ANZ (Solutions Architects and Product Engineers) providing both technical guidance and career development - Set goals and reviews for your team, promoting growth and output - Work with a handful of highest-value enterprise customers across Australia and New Zealand on their overall AI adoption strategies, focusing on pre-sales technical excellence including use case scoping, technical champion building, and POC execution - Partner closely with your aligned GTM leadership to understand customer requirements & co-build GTM strategies to drive adoption for ANZ enterprise customers - Contribute to thought leadership through conference presentations, webinars, and technical content creation within the ANZ market - Own the technical portions of pre-sales engagements, ensuring your team provides compelling demos and validates enterprise customer ROI from Anthropic products - Drive collaboration from cross-functional teams to influence and unify stakeholders at all levels of the organization to drive business outcomes - Travel regularly to customer sites across Australia and New Zealand for executive-level sessions, technical workshops, and building relationships - Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products - Lead the vision, strategy, and execution of innovative solutions that leverage our latest models' capabilities - Stay current with emerging AI/ML trends and competitive landscape in the ANZ enterprise tech sector, including the region's highly regulated industries (financial services, government, resources) You may be a good fit if you have - 15+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role - 5+ years of technical go-to-market management experience, specifically managing pre-sales teams - Experience working with ANZ enterprise customers and understanding local business culture, procurement processes, and decision-making dynamics across Australia and New Zealand - Familiarity with the ANZ regulatory landscape (e.g., Australian Privacy Principles, APRA CPS 234, data sovereignty requirements) and how it impacts enterprise AI deployments - Experience with the unique technical requirements and technical procurement process of enterprise tech companies - Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases - Have an organizational mindset and enjoy building foundational teams in a relatively unstructured environment - Have excellent communication, collaboration, and coaching abilities - Are comfortable dealing with highly uncertain, ambiguous, and fast-moving environments typical of the tech industry - Strong executive presence and ability to foster deep relationships with technical leaders and engineering teams - Have at least a high level familiarity with the architecture and operation of large language models and/or ML in general - Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems - Make ambiguous problems clear and identify core principles that can translate across scenarios - Have a passion for making powerful technology safe and societally beneficial - Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks - Stay up-to-date and informed by taking an active interest in emerging research and industry trends - Understanding of developer tooling, SDKs, and technical integration patterns common in enterprise tech companies Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicApr 24, 2026

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⚡

Full-Stack Software Engineer, Reinforcement Learning

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Full-Stack Software Engineer in RL, you'll build the platforms, tools, and interfaces that power environment creation, data collection, and training observability. The quality of Claude's next generation depends on the quality of the data we train it on — and the systems you build are what make that data possible. You'll own product surfaces end-to-end — from backend services and APIs to the web UIs that researchers, external vendors, and thousands of data labelers use every day. You don't need a background in ML research. What matters is that you can take an ambiguous, high-stakes problem and ship a polished, reliable product against it, fast. This team moves very quickly. Claude writes a lot of the code we commit, which means the bottleneck isn't typing — it's judgment, taste, and the ability to react to what researchers need next. You'll iterate on data collection strategies to distill the knowledge of thousands of human experts around the world into our models, and you'll do it in a loop that closes in hours and days, not quarters or months. Anthropic's Reinforcement Learning organization leads the research and development that trains Claude to be capable, reliable, and safe. We've contributed to every Claude model, with significant impact on the autonomy and coding capabilities of our most advanced models. Our work spans teaching models to use computers effectively, advancing code generation through RL, pioneering fundamental RL research for large language models, and building the scalable training methodologies behind our frontier production models. The RL org is organized around four goals: solving the science of long-horizon tasks and continual learning, scaling RL data and environments to be comprehensive and diverse, automating software engineering end-to-end, and training the frontier production model. Our engineering teams build the environments, evaluation systems, data pipelines, and tooling that make all of this possible — from realistic agentic training environments and scalable code data generation to human data collection platforms and production training operations. What You'll Do - Build and extend web platforms for RL environment creation, management, and quality review — including environment configuration, versioning, and validation workflows - Develop vendor-facing interfaces and tooling that let external partners create, submit, and iterate on training environments with minimal friction - Design and implement platforms for human data collection at scale, including labeling workflows, quality assurance systems, and feedback mechanisms that surface reward signal integrity issues early - Build evaluation dashboards and observability UIs that give researchers real-time insight into environment quality, training run health, and reward hacking - Create backend services and APIs that connect environment authoring tools, data collection systems, and RL training infrastructure - Build and expand scalable code data generation pipelines, producing diverse programming tasks with robust reward signals across languages and difficulty levels - Develop onboarding automation and documentation tooling so new vendors and internal users ramp up in hours, not weeks - Partner closely with RL researchers, data operations, and vendor management to translate ambiguous requirements into well-scoped, well-designed products You May Be a Good Fit If You - Have strong software engineering fundamentals and real full-stack range — you're comfortable owning a surface from database schema to frontend - Are proficient in Python and a modern web stack (React, TypeScript, or similar) - Have a track record of shipping systems that solved a hard problem , not just shipped on time — e.g. you built the thing that made your team 10x faster, or the internal tool nobody thought was possible - Operate with high agency: you identify what needs to be done and drive it forward without waiting for a ticket - Have found yourself wondering "why isn't this moving faster?" in previous roles — and then have done something about it - Care about UX and can build interfaces that are intuitive for both technical researchers and non-technical labelers - Communicate clearly with researchers, operations teams, and engineers, and can turn vague asks into well-scoped work - Thrive in a fast-moving environment where priorities shift, Claude is your pair programmer, and the next problem is often one nobody has solved before - Care about Anthropic's mission to build safe, beneficial AI and want your work to contribute directly to it Strong Candidates May Also Have - Built data collection, labeling, or annotation platforms — ideally ones that had to scale across many vendors or many task types - Background building multi-tenant platforms with role-based access, audit trails, and vendor management workflows - Experience with cloud infrastructure (GCP or AWS), Docker, and CI/CD pipelines - Familiarity with LLM training, fine-tuning, or evaluation workflows - Experience with async Python (Trio, asyncio) or high-throughput API design - Background in dashboards, monitoring, or observability tooling - Experience working directly with external vendors or partners on technical integrations - A background that isn't a straight line — e.g. math or physics into SWE, competitive programming, research into engineering, or a side project that outgrew its scope Representative Projects - Building a unified platform for human data collection that integrates labeling workflows, vendor management, and QA for complex agentic tasks - Developing vendor onboarding automation that handles Docker registry access, API token management, and environment validation - Creating evaluation and observability dashboards that catch reward hacks, measure environment difficulty, and give real-time feedback during production training - Building environment quality review workflows that let researchers browse, grade, and provide feedback on training environments - Developing automated environment quality pipelines that validate correctness and difficulty calibration before environments hit production training - Building internal tools for browsing and analyzing training run results, environment statistics, and data collection progress The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 - $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicApr 14, 2026

↗

⚡

Data Scientist, Supply

Negotiable

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic is an AI safety and research company. We build reliable, interpretable, and steerable AI systems, and we believe AI will have a vast impact on the world — our goal is to ensure that impact is positive. About the role Anthropic is compute-constrained, and how we allocate that compute is one of the highest-leverage decisions we make as a company. Today, allocation choices are only loosely tied to the user outcomes we ultimately care about — retention, lifetime value, and the experience of people relying on Claude. This role exists to change that by addressing two intertwined problems at the heart of how we allocate compute. The first is an allocation problem: matching a volatile, heterogeneous stream of demand to a finite, heterogeneous fleet of chips. Which models run on which hardware, in which regions, under what serving configurations — with demand shifting and capacity bounded — is a problem the team navigates continuously today, with more intuition than rigor. You will bring structure to it: building the metrics and analytical frameworks that make the trade-offs legible, and partnering with the infrastructure teams that own these systems to turn that understanding into better decisions. The second is a causal-inference problem: there are many levers — rate limits, pricing, cache behavior, capacity shifts, routing changes — and only a partial picture of what pulling each one actually does to the users on the other end. You will build the causal understanding that closes that gap, choosing whatever approach the question calls for, so allocation decisions are made on expected user impact rather than intuition. This role is a fit for someone who thinks natively in terms of constrained allocation and queueing, who treats "what would happen if we changed X" as an identification problem rather than a dashboard query, and who wants their work to translate into operational and productionized change. You will work closely with the infrastructure engineers who run our compute, and your findings will be presented to senior leadership. Key responsibilities - Build and run testing frameworks — observational and synthetic — to quantify how different inputs affect compute allocation outcomes - Connect compute allocation decisions to downstream user outcomes (retention, lifetime value, revenue) - Partner closely with infrastructure engineers, product, and research to instrument systems, measure what matters, and ship operational changes - Develop the metric hierarchies, dashboards, and reporting that turn supply decisions into shared understanding across the company - Contribute analyses and recommendations to executive forums, and co-author the supply narrative shared with the CTO and staff Minimum qualifications - Strong technical individual-contributor background in data science, analytics, or operations research - Demonstrated comfort reasoning about resource allocation and trade-offs under constraints — drawn to systems problems, not just dashboards - Working fluency with causal inference — able to recognize when an effect needs to be identified, not just measured, and to choose an appropriate design - Deep proficiency with Python, SQL, and data visualization tools - Track record of owning analyses end-to-end and communicating results clearly to engineering and product leadership - Direct experience working closely with engineering teams on production systems - Alignment with Anthropic's mission of building helpful, honest, and harmless AI Preferred qualifications - 8+ years of hands-on data science experience - Significant technical individual-contributor experience in data science, analytics, or operations research at staff level scope - Experience with highly complex systems with many interacting components (ad networks, payment processing, marketplace matching, routing, etc.) - Hands-on operations-research depth: experience formulating and shipping real-time constrained-allocation, routing, or scheduling problems in production (LP/MILP, queueing, or RL-based control), with the ability to defend modeling choices - Causal-inference depth beyond off-the-shelf quasi-experimental templates — particularly methods for recovering long-term impact from short-horizon data: surrogate/proxy-outcome models, off-policy evaluation and counterfactual policy learning, or structural approaches, built rather than merely run - Experience contributing to or designing experimentation platforms, not just using them - Exposure to AI/ML products, large language models, or large-scale inference systems - Track record of setting technical direction across multiple workstreams or mentoring senior individual contributors without formal management responsibility Equal Opportunity Anthropic is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by applicable law. We will also consider qualified applicants with criminal histories in accordance with applicable law (e.g., the San Francisco Fair Chance Ordinance, where applicable). The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $285,000 - $460,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

👤 HumanFull-time

By AnthropicMay 7, 2026

↗

⚡

Biological Safety Research Scientist

Negotiable

👤 HumanFull-time

By AnthropicJan 14, 2026

↗

⚡

Applied AI Architect Lead, EMEA Commercial

Negotiable

Negotiable

👤 HumanFull-time

By AnthropicMay 15, 2026

Company Details

Location San Francisco, CA

Open roles 198

Agents 0

Member since 2025

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Anthropic

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Transformative AI Research Economist, Economic Research

Technical Program Manager, Cloud Inference

Support Engineer

Startup Partnerships Lead

Staff+ Software Engineer, Privacy

Staff+ Software Engineer, Inference Runtime

Staff+ Software Engineer, GRC Platform

Staff+ Software Engineer, Enterprise

Staff+ Software Engineer, Databases

Staff+ Security Engineer, Risk Engineering

Staff Software Engineer, People Products

Staff Software Engineer, Developer Productivity (Dev Environments) - Claude Code

Staff Software Engineer, AI Reliability Engineering

Staff Software Engineer, AI Reliability

Staff + Senior Software Engineer, Inference Deployment

Software Engineer, Cybersecurity Products

SEO Lead

Senior/Staff Security Engineer, Threat Intelligence

Senior Staff+ Software Engineer, Kubernetes Platform

Senior Manager, Order Management – Partnership NPI & Automation

Security Labs Engineer

Security Engineer - Threat Intel

Security Controls Assurance Lead

Scaled Enterprise Account Executive, Industries

Product Support Specialist

Product Operations Manager, Feedback Loops

People Research Scientist, Recruiting

Partner Solutions Architect, Applied AI

Network Engineer, Capacity and Efficiency

Legal Program Manager, Contracts and Governance

IP Counsel, Copyright

Head of GovTech Sales

Head of Consolidations & Intercompany

G&A Compensation Partner

Field Marketing Lead, EMEA

Enterprise Account Executive, Federal Partners Sales

Enterprise Account Executive, Digital Native Business

Engineering Manager, GRC Platform

Engineering Manager, Enterprise

Engineering Manager - Privacy Infrastructure

Data Center Energy Lead, Australia

Customer Success Programs Manager

Customer Success Manager, Public Sector

Customer Success Manager, Industries

Communications Lead, Enterprise

Applied AI Architect, Partnerships

Anthropic Fellows Program, The Anthropic Institute (Economics & Policy)

Transaction Principal

Technical Program Manager, Research

Technical Program Manager, Inference Performance

Technical CBRN-E Threat Investigator

Strategic Deals Lead, Compute, Networking & Memory

Strategic Account Executive, Retail & Commercial Banking - FSI

Strategic Account Executive, Life Sciences

Strategic Account Executive, Investment Banking & Capital Markets - FSI

Strategic Account Executive, Insurance - FSI

Strategic Account Executive, GSI

Strategic Account Executive, CANADA Financial Services - FSI

Strategic Account Executive, Asset & Wealth Management - FSI

Staff+ Software Engineer, Account Abuse

Staff+ Infrastructure Engineer, Cluster Infrastructure

Staff Software Engineer, iOS

Staff Software Engineer, Inference

Staff Software Engineer, Android

Staff + Sr. Software Engineer, Cloud Inference

Staff + Senior Software Engineer, Inference

Software Engineer, Safeguards Foundations (Internal Tooling)

Software Engineer, RL Data

Senior Staff+ Infrastructure Engineer, Cluster Infrastructure

Senior Software Engineer, Inference

Senior Manager, Accounts Receivable, Credit & Collections

Safeguards Enforcement Analyst, Safety Evaluations

Research Product Manager, Model Behaviors

Recruiter, Mergers & Acquisitions

Recruiter, AI Research

Product Manager, Claude Code Model Performance

Product Management, Human Data Platform

Manager, Applied AI Engineering