Software Engineer, Safeguards Foundations (Internal Tooling)

About the role

The Safeguards team is responsible for the systems that detect, review, and act on misuse of Anthropic's models — work that sits at the very centre of our mission to develop AI safely. Within Safeguards, the Foundations team builds the platforms, infrastructure, and internal tools that the rest of the organisation depends on to do this well.

We are looking for a software engineer to own and extend the internal tooling that powers human review — the case management, labelling, investigation, and enforcement interfaces our analysts and policy specialists use every day. These are back-office tools, but they are anything but low-stakes: the speed, clarity, and reliability of this tooling directly determines how quickly Anthropic can identify harmful behaviour, make sound enforcement decisions, and feed signal back into model training. You'll work closely with Trust & Safety operations, policy, and detection-engineering teams to turn messy operational workflows into well-designed, durable software.

This is a hands-on, full-stack role for someone who enjoys building products for internal users, sweats the details of usability and correctness, and wants their engineering work to have a clear line to real-world safety outcomes.

Responsibilities

• Design, build, and maintain the internal review and enforcement tooling used by Safeguards analysts — including case queues, content review surfaces, decision/audit logging, and account-actioning workflows
• Understand user workflows and establish tooling for well processes that may be distributed across a number of tools and UIs
• Develop the ‘base layer’ of reusable APIs, data storage, and backend services that let new review workflows be stood up quickly and safely
• Partner with operations and policy teams to understand reviewer pain points, then translate them into clear product improvements that reduce handling time and decision error
• Integrate tooling with upstream detection systems and downstream enforcement infrastructure so that flagged behaviour flows cleanly from signal → human review → action
• Build in the guardrails that sensitive internal tools require: granular permissions, audit trails, data-access controls, and reviewer wellbeing features (e.g