Product Manager, Safe Access
Anthropic· Product Management, Support, & Operations
Hybrid (San Francisco, CA), Hybrid (New York City, NY)$305k - $385kFull-timePosted 4w ago
About the role
Product Manager responsible for ownership of the safe access primitives (accounts, access programs, verification, user APIs, and related tooling) across Anthropic surfaces, shaping end-to-end product strategy and experience for internal and external users in a 0-1 product space.
Responsibilities
- Own the product strategy and roadmap for the account and access primitives to enable provisioning with minimal support across teams and surfaces.
- Own the end-to-end experience of getting and managing access for internal stakeholders (research, model launches, safeguards, go-to-market) and external customers/partners, ensuring consistency across surfaces.
- Support the API designs and the UX of the access APIs platforms, resellers, and internal services; collaborate with engineering and make primitives decisions.
- Partner with trusted access and verification product managers to ensure programs compose from shared primitives.
- Coordinate across product, safeguards, legal, and go-to-market teams and drive alignment when requirements conflict.
Qualifications
- Are a strong executor with a track record of shipping through ambiguity and cross-organization dependencies.
- Write clearly for engineers, executives, and external partners to understand tradeoffs.
- Have owned a developer platform, identity, authorization, or access-management product end to end and been accountable for outcomes (typically five+ years as a PM, focus on ownership).
- Care about Anthropic's mission, and specifically about scaling access to Claude safely.
Skills
Required:Product strategy and roadmappingCross-functional collaborationUser experience design collaboration
Last updated Sep 23, 2026. Interested? Apply on the company site.
About Anthropic
building reliable, interpretable, and steerable AI systems
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
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