290K–435K USD / year

Technical Program Manager, Inference

AIHybrid — San Francisco, CA | New York City, NY | Seattle, WA
Published on 2026-10-15
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.

About this role

The Technical Program Manager will oversee the scaling and infrastructure of Anthropic's inference systems, driving the programs that enhance the serving fleet and toolchain efficiency. The role requires collaboration across multiple teams to optimize performance and ensure readiness for model launches.

About the company

Anthropic builds reliable and interpretable AI systems, including the Claude family of models, for businesses and developers. The company focuses on AI safety research and practical AI assistants for enterprise and consumer use.

What you'll do

  • Own programs that scale Claude’s serving fleet across platforms.
  • Drive new capacity online end to end.
  • Build visibility into supply, demand, and utilization.
  • Lead reliability programs and large migrations.
  • Drive productivity improvements for inference engineers.
  • Coordinate roadmaps across production and research needs.
  • Track performance and efficiency work in production.
  • Own inference readiness for model launches.

What we're looking for

  • 7+ years of experience as a TPM or in a lead engineering role.
  • Technical fluency in large-scale serving infrastructure.
  • Understanding of LLM inference and hardware.
  • Track record of building program mechanisms from scratch.
  • Ability to drive outcomes across competing priorities.
  • Strong written communication skills.
  • Low ego and high ownership.
  • Alignment with Anthropic's mission.

Nice to have

  • Experience with LLM or ML inference serving.
  • Experience with accelerator infrastructure.
  • Managing capacity across multiple clouds.
  • Experience with developer productivity and CI/CD.
  • Running performance efficiency programs.
  • Familiarity with Kubernetes-based orchestration.
  • Experience working with research teams.
  • Practical experience using AI tools.
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