Technical Program Manager, Compute (AI)

Location: San Francisco, CA; New York City, NY; or Seattle, WA. Hybrid work is required, with all staff expected to be in one of the offices at least 25% of the time.

Annual salary: $290,000–$365,000 USD

Company

Anthropic develops reliable, interpretable, and steerable AI systems intended to be safe and beneficial for users and society.

What you will do

• Own and drive critical programs across the compute lifecycle, coordinating engineering, research, and operations teams.
• Maintain visibility into compute supply, demand, utilization, health, and cost.
• Coordinate compute transitions, including bringing capacity online, migrating workloads, and managing decommissions across cloud providers and hardware platforms.
• Partner with Infrastructure, Systems, Research, Finance, and Capacity Engineering leaders to align resource planning and allocation.
• Identify operational gaps and improve tooling, processes, communication, and execution frameworks.
• Lead trade-off discussions involving utilization, cost, latency, and reliability, and communicate decisions to leadership.

Requirements

• 7+ years of technical program management experience in infrastructure, platform engineering, or compute-intensive environments.
• Experience leading complex cross-functional programs with multiple engineering teams, competing priorities, and ambiguous requirements.
• Experience working with research or ML teams and translating their needs into operational plans and technical requirements.
• Technical familiarity with cloud infrastructure, cluster management, job scheduling, and resource orchestration.
• Strong communication skills and the ability to work credibly with engineers, researchers, finance, and executive leadership.
• Bachelor’s degree or an equivalent combination of education, training, and relevant experience.

Nice to have

• Experience managing compute capacity across AWS, GCP, Azure, hybrid cloud, or on-premises environments.
• Familiarity with Kubernetes, Slurm, Borg, YARN, or custom schedulers.
• Experience with GPU or accelerator infrastructure and large-scale ML training and inference workloads.
• Experience building infrastructure observability, capacity plans, cost models, or hardware lifecycle programs.
• Experience scaling AI/ML, HPC, or large-scale cloud environments through hypergrowth.

Culture & Benefits

• Collaborative environment focused on a small number of large-scale AI research efforts.
• Frequent research discussions and emphasis on communication and cross-functional collaboration.
• Competitive compensation and benefits, including optional equity donation matching.
• Generous vacation and parental leave, flexible working hours, and an office environment designed for collaboration.
• Visa sponsorship is available, subject to role and candidate eligibility.