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Anthropic · Engineering · Lead / Manager · Posted 2026-06-10

Engineering Manager, Safeguards Review Tooling

Anthropic · San Francisco, CA · $405k–485k base

This is one of the highest posted engineering ranges at AI companies right now. See the salary index.

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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 an Engineering Manager to lead 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.

This is a foundational role: 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 analytics 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. As model capabilities and usage grow, you'll also drive how we scale review through automation — building systems where Claude meaningfully extends what human reviewers can do, while keeping people in the loop where their judgment matters most.

You'll partner closely with policy, operations, data science, and legal teams to ensure our enforcement systems are effective, accurate, and trustworthy.

Key responsibilities

Lead, grow, and develop a team of engineers building investigation, review, and enforcement tooling for both first-party and third-party platform surfaces

Define the vision and roadmap for our review tooling platform, including analytics, privacy-compatible data access primitives, and a sandbox for rapidly developing new review interfaces

Drive the team's strategy for scaling 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

Ensure review tooling evolves alongside new privacy primitives and data retention commitments, so reviewers can do their work without compromising user trust

Create clarity for the team and stakeholders in an ambiguous and evolving environment

Take an inclusive, equitable approach to hiring and coaching top technical talent, and maintain a high-performing team

Contribute to engineering-wide initiatives as a member of Anthropic's engineering management community

Minimum qualifications

Experience managing software engineering teams, including hiring, coaching, and developing engineers

A technical background in full-stack or platform engineering, with the ability to engage deeply in architecture and design discussions

Experience shipping internal tools or platforms with demanding operational users, and a track record of improving their workflows measurably

Experience working cross-functionally with non-engineering partners such as operations, policy, or legal teams

Excellent communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders

Care about the societal impacts of AI and want your work to make powerful systems safer

Preferred qualifications

4+ years of management experience, 10+ years of industry software engineering experience

Experience building trust and safety, integrity, fraud, or abuse-prevention tooling, or other systems supporting human review at scale

Experience designing systems under strict privacy, compliance, or data governance constraints, such as zero data retention environments

Experience integrating LLMs or agentic systems into operational workflows, or bu …

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