Principal Engineer Capacity/Compute

Details

Anthropic's Capacity Engineering team builds the data, tooling, and operational systems used to account for, utilize, and allocate infrastructure resources across accelerator families, CPU families, and cloud providers. This role focuses on production systems supporting data engineering, systems engineering, observability, capacity planning, efficiency, attribution, and forecasting.

Responsibilities

• Build the planning and allocation stack for capacity allocation, team planning, scheduler enforcement, cross-region and cross-provider placement, guardrails, queueing, and occupancy KPIs.
• Drive efficiency programs covering stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and evaluation workloads.
• Establish per-configuration utilization baselines and collaborate with system-owning teams to improve efficiency.
• Reconcile billing across more than ten providers with telemetry and internal systems, attribute spend to workloads, and convert demand signals and research roadmaps into compute plans and supply pipelines.
• Build data pipelines ingesting occupancy, utilization, and cost data into BigQuery, with ownership of completeness, latency SLOs, and gap detection.
• Operate Kubernetes-native systems at scale, including collection agents, workload labeling, taints, reservations, and scheduling behavior.
• Define schema contracts, gather requirements, design self-service data products, and support consumers ranging from research engineers to finance and company leadership.
• Build observability tooling, including real-time fleet health visibility and performance instrumentation for measuring workload efficiency.
• Collaborate with research engineering, infrastructure, inference, and finance teams in a high-autonomy, high-ambiguity environment.

Requirements

• Strong track record building and operating production systems in a hands-on engineering role with a DevOps flavor.
• Production-quality Python and SQL experience. Pipeline code is primarily Python, while the presentation layer uses BigQuery SQL, including table-valued functions and views.
• Deep experience with at least one major cloud provider: Amazon Web Services, Google Cloud, or Microsoft Azure.
• Experience with observability tooling, including Prometheus, PromQL, and Grafana; recording rules and monitoring relied upon by engineering teams.
• Ability to gather requirements independently and work across organizational boundaries with limited direction.
• Bachelor's degree or equivalent combination of education, training, and experience.
• A relevant field of study demonstrated through coursework, training, or professional experience.

Preferred Qualifications

• Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment.
• Scheduling and packing efficiency experience or profiling-driven optimization of large distributed workloads.
• Multi-cloud data ingestion experience, including billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry.
• Total cost of ownership and forecasting experience.
• Accelerator infrastructure experience, including GPU metrics such as DCGM, TPU utilization, Trainium power and utilization metrics, or hardware-level machine learning training and inference systems.
• Experience building internal data products with self-service access, schema contracts, APIs, documentation, and discoverability.
• Storage efficiency, retention, and lifecycle program experience at exabyte scale.

Compensation

Annual salary: $320,000–$485,000 USD.

Logistics

The role has a location-based hybrid policy, with staff expected to be in an office at least 25% of the time. The application states that the role requires on-site presence three to four times per week, with no remote option, and can be based in San Francisco, Seattle, or New York City. Anthropic explicitly states that it sponsors visas and will make reasonable efforts to obtain a visa for candidates who receive an offer.