Staff+ Software Engineer, Capacity Engineering

Details

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The Capacity Engineering team ensures infrastructure resources are accounted for, well-utilized, and efficiently allocated across accelerator families, CPU families, and clouds. As an engineer on Capacity Engineering you will build production systems: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling for real-time fleet visibility, and performance instrumentation to measure workload efficiency. You will write production-quality code, operate Kubernetes-native infrastructure at scale, and influence decisions around one of Anthropic’s largest areas of spend.

Responsibilities

• Build planning and allocation tooling used by leadership and teams: cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs, and scheduler-enforced allocations.
• Drive efficiency programs: identify and remediate stranding and rightsizing, recover unused capacity, and improve job-level utilization across training, inference, and eval.
• Own attribution and forecasting: reconcile billing across many providers with telemetry and internal systems, attribute spend to workloads/teams, and turn demand signals and roadmaps into a compute plan.
• Build and operate the data platform: pipelines that ingest occupancy, utilization, and cost data into BigQuery with ownership of completeness, latency SLOs, and gap detection.
• Operate Kubernetes-native systems at scale: collection agents, workload labeling, taint/reservation/scheduling behavior affecting usable capacity.
• Treat outputs as product surfaces: gather requirements, define schema contracts, design for consumers including research engineers and finance, and run on-call/SLOs for load-bearing systems.

Requirements

• Strong track record building and operating production systems; hands-on engineering with a DevOps flavor.
• Production-quality Python and SQL; experience authoring 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) and its operations.
• Experience with observability tooling: Prometheus, PromQL, and Grafana (including writing recording rules and building monitoring relied upon by engineering teams).
• Ability to gather requirements and work across organizational boundaries in ambiguous environments.

Preferred qualifications

• Experience with capacity planning, resource management, or cost attribution systems in large-scale ML environments or at a hyperscaler.
• Scheduling and packing efficiency experience or profiling-driven optimization of large distributed workloads.
• Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, commitments, and vendor telemetry from differing billing arrangements.
• Total cost of ownership and forecasting experience; decomposing infrastructure growth vs business drivers.
• Accelerator infrastructure familiarity (GPU metrics/DCGM, TPU utilization, Trainium metrics) or ML training/inference systems at the hardware level.
• Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability.
• Storage efficiency, retention, and lifecycle program experience at exabyte scale.

Logistics & Compensation

• Locations: San Francisco, CA; New York City, NY; Seattle, WA.
• Location-based hybrid policy: staff expected to be in an office at least 25% of the time.
• Minimum education: Bachelor’s degree or equivalent experience.
• Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist when possible.
• Annual salary range: $320,000 - $485,000 USD.