Anthropic
Principal Engineer Capacity/Compute
$320K–$485K
New York City, NY +1 · Principal · Full-time · Posted Oct 18, 2026
- Location
- New York City, NY
San Francisco, California, United States - Experience
- Years required correlate with internal job level; no specific number stated.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; the company says it will make every reasonable effort to obtain a visa if it makes an offer.
About the job
Build and operate production systems for planning, allocating, measuring, and attributing Anthropic’s compute capacity across cloud providers and infrastructure fleets.
What you'll do
- Build capacity planning, allocation, efficiency, attribution, and forecasting systems, including tools, metrics, and integrations.
- Develop data pipelines that ingest fleet telemetry and cost data into BigQuery, with ownership of completeness, latency, and gap detection.
- Operate Kubernetes-native systems and observability; define product requirements and schema contracts for internal consumers.
What they ask for
- Track record building and operating production systems.
- Production-quality Python and SQL skills.
- Deep operational 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.
Nice to have
- Experience in capacity planning, resource management, cost attribution, scheduling, or large-scale distributed workload optimization.
- Multi-cloud data ingestion, forecasting, accelerator infrastructure, or internal data product experience.
Pay
$320,000 — $485,000 USD annual base salary
Tools
Python, SQL, BigQuery, Kubernetes, Prometheus, PromQL, Grafana, Amazon Web Services
AI focus
No direct AI development stated; the role supports compute infrastructure used for training, inference, and evaluation systems.
Model-written summary · the original posting is authoritative