Technical Program Manager, Compute en Anthropic

Híbrido - San Francisco, CA

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As a Technical Program Manager on the Compute team, you will help drive the planning, coordination, and execution of programs that keep Anthropic's compute infrastructure running efficiently at scale. Our compute fleet is the foundation on which every model training run, evaluation, and inference workload depends. You'll join a small, high‑impact TPM team and take ownership of critical workstreams across the compute lifecycle, from how supply is procured and brought online, to how capacity is allocated and utilized across teams.

Salary

USD 290,000 - 365,000

Requirements

Skills

  • 7+ years of technical program management experience in infrastructure, platform engineering, or compute-intensive environments
  • Led complex, cross-functional programs involving multiple engineering teams with competing priorities and ambiguous requirements
  • Experience working with research or ML teams and translating their needs into operational plans and technical requirements
  • Comfortable diving deep into technical details (cloud infrastructure, cluster management, job scheduling, resource orchestration) while maintaining program-level visibility
  • Thrives in ambiguous, fast-moving environments where scope must be defined and processes built from the ground up
  • Strong communication skills and ability to engage credibly with engineers, researchers, finance, and executive leadership
  • Track record of building trust with engineering teams and driving changes through influence rather than authority
  • Bachelor’s degree or an equivalent combination of education, training, and/or experience

Responsibilities

  • Own and drive critical programs across the compute lifecycle, coordinating execution across multiple engineering, research, and operations teams
  • Build and maintain operational visibility into the compute fleet, ensuring the organization has a clear picture of supply, demand, utilization, and health
  • Lead cross-functional coordination for compute transitions: bringing new capacity online, migrating workloads, and managing decommissions across cloud providers and hardware platforms
  • Partner with engineering and research leadership to navigate competing priorities and drive alignment on how compute resources are planned, allocated, and used
  • Identify and close operational gaps across the compute pipeline, whether through new tooling, improved processes, or better cross-team communication
  • Own trade‑off discussions between utilization, cost, latency, and reliability, synthesizing inputs from technical and business stakeholders and communicating decisions to leadership
  • Develop and improve the processes and frameworks the team uses to plan, track, and execute compute programs at increasing scale and complexity

Technologies

AWSGCPAzureHybrid cloud/on-premises environmentsKubernetesSlurmBorgYARNGPU or accelerator infrastructureJob schedulingResource orchestrationCluster managementDashboardsAlertingEfficiency metricsCost attributionCapacity planning

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