Safeguards Policy Analyst, Fraud & Scams

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 risk areas

Stakeholder Alignment & Education

• Educate and align internal stakeholders — including Legal, Public Policy, and Go-to-Market teams — around Anthropic's fraud and scams policies and enforcement approach
• Serve as an internal resource on fraud risk, briefing leadership and cross-functional partners as threats evolve
• Contribute to Anthropic's external communications and policy documentation related to fraud and platform integrity where relevant

You may be a good fit if you have experience:

• Working as a Trust & Safety professional with a focused background in fraud, scams, or financial crime — particularly in a tech platform or AI context
• Writing, iterating on, and managing operational policies for fraud or abuse prevention at scale
• Threat modeling for fraud and scam ecosystems, including social engineering, romance scams, investment fraud, impersonation, and phishing
• Identifying and articulating common fraud tactics (e.g., pig butchering, advance fee fraud, account takeover facilitation) and how they manifest on AI platforms
• Using SQL or other data analysis tools to identify trends, measure enforcement efficacy, and surface policy gaps
• Collaborating cross-functionally with Engineering, ML, Legal, and Policy teams on safety initiatives
• Working with generative AI products, including writing effective prompts for content review and enforcement use cases
• Thriving in a fast-paced, ambiguous environment where priorities shift and the threat landscape evolves rapidly

Preferred Qualifications:

• Experience at a major technology platform, financial institution, or fraud intelligence firm in a policy, operations, or investigative capacity
• Familiarity with the generative AI risk landscape and how large language models can be exploited for fraud and social engineering
• Background in threat intelligence, financial crimes compliance (AML/KYC), or law enforcement focused on cyber-enabled fraud
• Demonstrated ability to develop and communicate policy positions to diverse stakeholders including legal counsel and executive leadership