Senior Engineering Manager, Capacity Engineering

Location: San Francisco, CA; New York City, NY; or Seattle, WA. Hybrid attendance is required at least 25% of the time.

Annual salary: $405,000–$485,000 USD

Company

Anthropic develops reliable, interpretable, and steerable AI systems designed to be safe and beneficial.

What you will do

• Lead, hire, coach, and develop senior and staff-level engineers responsible for capacity engineering.
• Set the roadmap across data platforms, capacity planning, operational assurance, and infrastructure efficiency.
• Oversee pipelines that process occupancy, utilization, billing, and usage telemetry across Kubernetes clusters and cloud providers.
• Build systems for cluster health, capacity planning, allocation monitoring, benchmarking, and workload efficiency.
• Set production standards for Python and SQL systems, data quality, SLOs, incident response, and sustainable on-call practices.
• Partner with infrastructure, inference, research engineering, finance, and senior leadership on capacity decisions, efficiency targets, and spend.

Requirements

• Experience managing software or infrastructure engineering teams, including hiring, performance management, and people development.
• Strong hands-on background in production systems, data engineering, infrastructure, distributed systems, or observability.
• Experience with at least one major cloud provider, Kubernetes-based infrastructure, and observability tools such as Prometheus or Grafana.
• Experience setting and executing engineering roadmaps in ambiguous, high-autonomy environments with multiple stakeholders.
• Excellent communication skills and experience owning on-call and incident management for business-critical systems.
• Bachelor’s degree or equivalent education, training, or professional experience in a relevant field.

Nice to have

• Experience with capacity planning, resource management, product engineering, or FinOps in hyperscale or large-scale ML environments.
• Familiarity with accelerator infrastructure, including GPU metrics, TPU utilization, and ML training or inference systems.
• Experience with multi-cloud billing, telemetry normalization, internal data products, scheduling, packing efficiency, or profiling-driven optimization.

Culture & Benefits

• Collaborative environment focused on large-scale AI research and trustworthy AI systems.
• Flexible working hours and regular research discussions.
• Competitive compensation, optional equity donation matching, generous vacation, and parental leave.
• Visa sponsorship is available, with immigration-lawyer support, although sponsorship is evaluated for each role and candidate.