2 months ago
Base Salary
$320k - $485k/yr
Responsibilities
- Build planning and allocation systems for cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs, and scheduling enforcement.
- Drive efficiency programs covering stranding, rightsizing, unused-capacity recovery, job-level utilization, configuration baselines, and workload optimization.
- Own cost attribution and forecasting by reconciling provider billing with telemetry, attributing spend to workloads and teams, and converting demand signals into compute plans.
- Build and own data pipelines that ingest occupancy, utilization, and cost data into BigQuery, including provider integrations, completeness, latency SLOs, and gap detection.
- Operate Kubernetes-native collection agents, workload labeling, and taint, reservation, and scheduling behavior at scale.
- Design internal data products with schema contracts, discoverability, documentation, self-service access, on-call coverage, and SLOs for consumers ranging from research engineers to finance leadership.
Requirements
- Build and operate production systems with a hands-on engineering and DevOps-oriented approach.
- Write production-quality, idiomatic, well-tested, and maintainable Python and SQL, including BigQuery SQL, table-valued functions, and views.
- Have deep experience operating at least one major cloud provider: Amazon Web Services, Google Cloud, or Microsoft Azure.
- Have experience with Prometheus, PromQL, and Grafana, including recording rules and monitoring relied upon by engineering teams.
- Gather requirements independently and work effectively across organizational boundaries in an ambiguous environment with limited direction.
- A bachelor’s degree or an equivalent combination of education, training, and/or experience is required in a relevant field demonstrated through coursework, training, or professional experience.
- Preferred qualifications include capacity planning, resource management, cost attribution, scheduling and packing efficiency, profiling-driven optimization, multi-cloud data ingestion, billing reconciliation, total-cost-of-ownership analysis, forecasting, accelerator infrastructure, machine-learning systems at the hardware level, internal data products, and exabyte-scale storage lifecycle programs.
Benefits
- Competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space are offered.
- Hybrid work is expected, with staff currently working from an office at least 25% of the time, though some roles may require more.
- Visa sponsorship may be available, with immigration-lawyer support, depending on the role and candidate.
- The role is a full-time staff position; no contract or internship duration is stated.
Tech Stack
Categories
Data EngineeringDevOps
About Anthropic
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.