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.
Anthropic's Safeguards team is responsible for enforcing our policies, protecting users, and ensuring our platform is not misused. As a Safeguards Enforcement Analyst focused on Safety Evaluations, you'll play a central role in ensuring our models meet safety and policy standards before and after launch.
What you'd do
- Support model launch readiness by running evaluations, monitoring and interpreting results, and surfacing regressions or unexpected behavior changes to relevant stakeholders
- Partner closely with policy and domain experts throughout the evaluation lifecycle — from identifying risks and scoping the right evaluation approach, to coordinating creation of new evals and ensuring existing ones remain current with evolving policies, threat vectors, and model capabilities
- Work with cross-functional stakeholders to help manage evaluation outcomes, including interpreting results and driving mitigations where needed
- Think strategically about eval quality to build processes and eval paradigms that keep evaluations unsaturated, high-signal, and insightful as models improve
- Build out processes and frameworks for creating product-specific evaluations as Anthropic's product surface area expands
- Help design and scope tooling improvements that accommodate evolving eval needs and expand self-serve eval creation and iteration for non-technical users
- Write and maintain rigorous documentation for evaluation creation, execution, and interpretation as the team builds out eval tooling and processes
- Have experience in trust and safety, content operations, policy enforcement, or a related operational role at a technology company
- Thrive in ambiguous, fast-moving environments — you're energized rather than frustrated when the path forward isn't clearly defined and you need to figure it out as you go
- Have experience building processes, workflows, or programs from scratch (zero-to-one work), not just maintaining existing ones