Description
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 Safeguards Policy Analyst focused on Fraud & Scams, you will be responsible for designing, building, and executing enforcement workflows that detect and mitigate fraud and scam-related harms on Anthropic's products. You will serve as the subject matter expert on fraud typologies, scam ecosystems, and the threat actors who perpetrate them — translating that expertise into durable and scalable policies. This role sits within the Integrity & Authenticity (I&A) team, You will function both as a policy owner, and work closely with threat investigative and enforcement teams. You will also develop the guidelines that power classifiers, and will be our point of content cross-functional workstreams. No two days will look the same. Important context: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a financial, psychological, or otherwise disturbing nature, including detailed fraud schemes and scam content. Responsibilities: Policy Design & Ownership - Draft, maintain, and iterate on Fraud & Scams policies governing Anthropic's products and APIs, with clarity for both model enforcement and human reviewers - Conduct regular structured policy reviews to identify gaps, ambiguities, and coverage failures, and lead the process to close them - Develop detailed threat models for fraud and scam vectors — including social engineering, financial fraud, impersonation scams, phishing, and AI-enabled fraud — and translate these into enforceable policy language - Stay current on the fraud and scam landscape, including emerging typologies, regulatory shifts, and threat actor tactics, techniques, and procedures (TTPs) Enforcement Strategy & Operations - Design and architect automated enforcement systems and human review workflows that scale effectively while maintaining high precision and recall - Review flagged content to drive enforcement decisions and surface policy improvements grounded in real-world cases - Define and manage precision/recall tradeoffs in enforcement, working with data science teams to continuously tune classifiers and detection signals - Build and maintain an effective feedback loop between threat intelligence, policy, and enforcement operations to ensure timely response to novel and evolving fraud threats Technical & Cross-functional Collaboration - Serve as the primary policy point of contact for ML and Engineering teams developing fraud detection classifiers, working to translate policy intent into technical artifacts and training signals - Partner with Product, Engineering, and Data Science teams to optimize detection models, automated enforcement pipelines, and tooling for fraud-specific policy violations - Collaborate with external researchers, law enforcement liaisons, and fraud SMEs to gather feedback on policy effectiveness and emerging ris