Staff+ Software Engineer, Capacity Engineering

About the Role

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.

As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on.

You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams.

The work requires someone who can move between data engineering, systems engineering, and observability with comfort , and who thrives in a high-autonomy, high-ambiguity environment.

This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap:

• Data platform: Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against.
• Planning: Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time.
• Efficiency: Measuring and improving how effectively every major workload uses the hardware it runs on.
• Attribution and forecasting: Connecting what the fleet costs to what the business is doing with it.

Key Responsibilities

• 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.
• Operate Kubernetes-native systems at scale , collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable.

What You Bring

• A strong track record building and operating production systems.
• 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.
• Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction.

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, 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.
• Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability.

Logistics

• Annual Salary: $320,000-$485,000 USD