Staff+ Software Engineer, Safeguards Human Review Tooling

San Francisco, CA · full time · Staff

$320,000 – $485,000

Listed on Menlo Ventures Portfolio’s own careers site. You apply with them directly — we never stand between you and the employer.

What this role is

This role builds internal tooling and platforms for investigating and addressing harmful behavior across Anthropic's AI products, combining full-stack engineering with cross-functional work across policy, legal, and operations teams. It suits experienced platform engineers who want to apply their skills directly to AI safety and can thrive in roles that serve non-technical stakeholders rather than end users.

Our summary, not Menlo Ventures Portfolio’s wording. The full posting is on their site.

Skills this role names

What they ask for

Required

Full-stack or platform engineering background with ability to engage in architecture and design discussions
Experience shipping internal tools or platforms with demanding operational users and measurably improving their workflows
Cross-functional work with non-engineering partners such as operations, policy, or legal teams
Excellent communication skills including explaining technical tradeoffs to non-technical stakeholders
Care about the societal impacts of AI and commitment to making powerful systems safer

Nice to have

8+ years of industry software engineering experience
Experience building trust and safety, integrity, fraud, or abuse-prevention tooling, or 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 building human-in-the-loop automation
Experience building developer platforms or extensible tooling frameworks that other teams build on top of
Experience supporting enforcement or moderation systems across multiple product surfaces including enterprise or cloud platform contexts
Product-minded approach to internal users with direct engagement and iteration based on user struggles