Safeguards Policy Analyst, Fraud & Scams Remote-Friendly (Travel-Required) | San Francisco, CA [...]

Remote‑Friendly (Travel‑Required) | San Francisco, CA | New York City, NY 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 develop the guidelines that power classifiers, and will be the point of contact for cross‑functional content workstreams. Important context: In this position you may be exposed to and engage with explicit content spanning a range of topics, 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 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 Compensation Annual compensation range: $245,000 – $285,000 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. If we make you an offer, we will make every reasonable effort to obtain a visa. EEO Statement As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. #J-18808-Ljbffr Anthropic