Technical Program Manager, Compute at Anthropic

Hybrid - San Francisco, CA; New York City, NY; Seattle, WA

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Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. As a Technical Program Manager on the Compute team, you will drive planning, coordination, and execution of programs that keep Anthropic’s compute infrastructure running efficiently at scale, partnering with cross‑functional teams across infrastructure, systems, research, finance, and capacity engineering.

Salary

USD 290,000 - 365,000

Requirements

Skills

  • Have 7+ years of technical program management experience in infrastructure, platform engineering, or compute-intensive environments
  • Have led complex, cross-functional programs involving multiple engineering teams with competing priorities and ambiguous requirements
  • Have experience working with research or ML teams and translating their needs into operational plans and technical requirements
  • Are comfortable diving deep into technical details (cloud infrastructure, cluster management, job scheduling, resource orchestration) while maintaining program-level visibility
  • Thrive in ambiguous, fast-moving environments where you need to define scope and build processes from the ground up
  • Have strong communication skills and can engage credibly with engineers, researchers, finance, and executive leadership
  • Have a track record of building trust with engineering teams and driving changes through influence rather than authority
  • Experience managing compute capacity across multiple cloud providers (AWS, GCP, Azure) or hybrid cloud/on-premises environments
  • Familiarity with job scheduling, resource orchestration, or workload management systems (Kubernetes, Slurm, Borg, YARN, or custom schedulers)
  • Experience with GPU or accelerator infrastructure, including the unique challenges of large-scale ML training and inference workloads
  • Built or improved observability for infrastructure systems: dashboards, alerting, efficiency metrics, or cost attribution
  • Capacity planning experience including demand forecasting, cost modeling, or hardware lifecycle management
  • Scaled through hypergrowth in AI/ML, HPC, or large-scale cloud environments

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

AWSGCPAzureKubernetesSlurmBorgYARNGPUAccelerator infrastructureCompute infrastructureJob schedulingResource orchestration

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