Technical Program Manager, Compute

San Francisco, CA | New York City, NY | Seattle, WAFull-TimeManagerProduct / Project

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Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

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. The exact focus will depend on your strengths and the team's evolving needs.
You'll partner with Infrastructure, Systems, Research, Finance, and Capacity Engineering to shape the processes, tooling, and coordination mechanisms that allow Anthropic to move fast while managing an increasingly complex compute environment.

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

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-premise 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

The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.