Staff+ Software Engineer, Safeguards Human Review Tooling

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

The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for engineers for our Review Tooling team, which builds the systems that humans — and increasingly Claude — use to investigate potential harms and take enforcement actions across Anthropic's first-party products and third-party cloud platforms.

You'll own the tools our safety investigators rely on to understand what's happening on our platforms and act on it, as well as the platform underneath those tools. That platform includes data analysis capabilities, privacy-preserving primitives that keep review workflows compatible with our data retention commitments, and a sandbox environment where new review interfaces and workflows can be built and iterated quickly.

These are internal tools, but they are anything but low-stakes: the speed, clarity, and reliability of this tooling directly determines how quickly Anthropic can identify harmful behavior, make sound enforcement decisions, and feed signals back into model training and safety classifiers. You'll partner closely with policy, operations, data science, legal, and privacy teams to ensure our enforcement systems are effective, accurate, and trustworthy.

Key responsibilities

• Build investigation, review, and enforcement tooling for both first-party and third-party platform surfaces — including case queues, investigation views, decision and audit logging, and account-actioning workflows
• Develop the platform layer of reusable APIs, data storage, and backend services that lets new review workflows be stood up quickly and safely
• Stand up and run deployments of this tooling across multiple clouds, including inside cloud-provider partner environments where data must stay in place. Keep the deployments consistent through shared deployment pipelines, smoke tests, observability, and alerting
• Scale review through automation, including enabling reviewers to use Claude effectively and building toward Claude-assisted and Claude-driven review workflows
• Partner with policy, operations, legal, privacy, and data science stakeholders to translate enforcement and investigation needs into reliable, well-designed systems that measurably reduce handling time and decision error
• Instrument the tools you ship — surfacing metrics on queue health, reviewer throughput, and decision quality — and ensure tooling evolves alongside new privacy pri