320K–485K USD / year
Principal Engineer, Capacity/Compute
DevOpsHybrid — Seattle, WA
Published on 2026-10-19
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.
About this role
Build and operate production systems that help Anthropic plan, measure, and efficiently allocate its large, multi-cloud compute fleet. The role spans capacity planning, utilization measurement, cost attribution and forecasting, and the data platform that supports these functions.
About the company
Anthropic builds reliable and interpretable AI systems, including the Claude family of models, for businesses and developers. The company focuses on AI safety research and practical AI assistants for enterprise and consumer use.
The team
Capacity Engineering
Stack
PythonSQLBigQueryKubernetesPrometheusPromQLGrafana
What you'll do
- Build capacity planning and allocation tools, including placement, queueing, and occupancy tracking.
- Measure and improve utilization across training, inference, and evaluation workloads.
- Reconcile cloud billing with telemetry and internal systems, attribute costs, and forecast compute demand.
- Build reliable data pipelines for occupancy, utilization, and cost data in BigQuery.
- Operate Kubernetes-native collection, labeling, reservation, and scheduling systems.
- Define data contracts and deliver dependable, discoverable products for engineering, finance, and leadership.
What we're looking for
- Track record building and operating production systems, with hands-on engineering and operational experience.
- Production-quality Python and SQL skills.
- Deep experience with at least one major cloud provider: AWS, Google Cloud, or Azure.
- Experience with Prometheus, PromQL, and Grafana, including recording rules and production monitoring.
- Ability to independently gather requirements and work across teams in ambiguous environments.
Nice to have
- Experience in capacity planning, resource management, or cost attribution at large scale.
- Scheduling, packing efficiency, or profiling-driven optimization of distributed workloads.
- Multi-cloud billing and telemetry data integration experience.
- Total-cost-of-ownership analysis and infrastructure forecasting experience.
- Familiarity with accelerator infrastructure, GPU/TPU/Trainium metrics, or ML systems.
- Experience building self-service internal data products or managing storage efficiency at exabyte scale.
Benefits
- Flexible working hours
- Generous vacation and parental leave
- Optional equity donation matching