Safeguards Policy Analyst, Fraud & Scams

About Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. The 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 develop the guidelines that power classifiers and serve as a point of contact for cross-functional workstreams.

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.

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