Safeguards Policy Analyst, Fraud & Scams

Anthropic Anthropic · AI Frontier · United States · Remote · Safeguards (Trust & Safety)

This role focuses on designing, building, and executing enforcement workflows to detect and mitigate fraud and scam-related harms on Anthropic's AI products. The analyst will act as a subject matter expert on fraud typologies, translating this expertise into scalable policies and working closely with threat investigative and enforcement teams. They will also develop guidelines for classifiers and collaborate with ML/Engineering teams.

What you'd actually do

  1. Draft, maintain, and iterate on Fraud & Scams policies governing Anthropic's products and APIs, with clarity for both model enforcement and human reviewers
  2. Design and architect automated enforcement systems and human review workflows that scale effectively while maintaining high precision and recall
  3. 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
  4. Partner with Product, Engineering, and Data Science teams to optimize detection models, automated enforcement pipelines, and tooling for fraud-specific policy violations
  5. Stay current on the fraud and scam landscape, including emerging typologies, regulatory shifts, and threat actor tactics, techniques, and procedures (TTPs)

Skills

Required

  • SQL or other data analysis tools
  • Writing, iterating on, and managing operational policies for fraud or abuse prevention at scale
  • Threat modeling for fraud and scam ecosystems
  • Identifying and articulating common fraud tactics
  • 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

Nice to have

  • 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

What the JD emphasized

  • fraud and scam-related harms
  • fraud typologies
  • scam ecosystems
  • threat actors
  • automated enforcement systems
  • human review workflows
  • precision and recall
  • fraud detection classifiers
  • fraud-specific policy violations
  • fraud and scams policies
  • fraud risk
  • fraud, scams, or financial crime
  • fraud or abuse prevention
  • fraud and scam ecosystems
  • AI platforms
  • fraud detection
  • fraud intelligence
  • generative AI risk landscape
  • LLMs can be exploited for fraud

Other signals

  • Designing and architecting automated enforcement systems
  • Define and manage precision/recall tradeoffs in enforcement
  • Serve as the primary policy point of contact for ML and Engineering teams developing fraud detection classifiers