Principal Engineer Capacity/Compute

San Francisco · USD 320,000-485,000 / year · Hybrid · Posted Oct 18, 2026

At a glance

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.

Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry spanning multiple accelerator families, cpu families and clouds.
The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated, owning the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute.

Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces.
Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval.
Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline.
Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection.
Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable.
Treat the output as a product, not a pipeline by gathering your own requirements, defining schema contracts, and designing for consumers ranging from research engineers to a CFO.

A strong track record building and operating production systems with a devops flavor.
Python and SQL at production quality.
Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations.
Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on.
Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience.

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, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements.
Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers.
Accelerator infrastructure familiarity including GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and 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.

Location-based hybrid policy: currently, we expect all staff to be in one of our offices at least 25% of the time, though some roles may require more time in our offices.