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About the Role
The Capacity Engineering team is responsible for ensuring all infrastructure resources are accounted for, well-utilized, and efficiently allocated. This role leads the team that builds and operates these production systems, setting technical direction, growing a team of senior and staff-level engineers, and ensuring the reliability and correctness of critical systems. The work spans data platform, planning and assurance, and efficiency improvements across training, inference, and evaluation workloads.
Responsibilities
- Lead and grow the team, including hiring, coaching, and retaining senior and staff engineers.
- Own the roadmap, translating company-level compute strategy into a prioritized engineering roadmap.
- Set the technical bar by reviewing designs, weighing in on architecture, and upholding production standards.
- Run the team as a product organization, ensuring requirements gathering, schema contract definition, and design for diverse consumers.
- Act as the primary partner for cross-functional stakeholders, aligning on capacity decisions, efficiency targets, and spend attribution.
- Drive operational excellence, owning reliability and incident response for load-bearing systems.
- Scale the function by anticipating growth needs in headcount, skills, and systems.
Requirements
- Experience managing software or infrastructure engineering teams, including hiring senior engineers, managing performance, and developing people.
- Strong technical background in production systems (data engineering, infrastructure, distributed systems, or observability) with hands-on experience.
- Familiarity with at least one major cloud provider (AWS, GCP, or Azure), Kubernetes-based infrastructure, and modern observability stacks.
- Track record of setting and executing an engineering roadmap in an ambiguous, high-autonomy environment.
- Excellent communication skills, capable of explaining technical concepts to diverse audiences.
- Comfort owning operational responsibility for systems, including on-call and incident management.
- Bachelor’s degree or an equivalent combination of education, training, or experience.
- Required field of study: A field relevant to the role.
- Minimum years of experience will correlate with internal job level requirements.
Skills
- Python
- SQL
- AWS
- GCP
- Azure
- Kubernetes
- Prometheus
- Grafana
- Capacity planning
- Resource management
- Cost attribution
- FinOps
- Accelerator infrastructure
- GPU metrics (DCGM)
- TPU utilization
- ML training and inference systems
- Multi-cloud billing
- Telemetry normalization
- Scheduling
- Packing efficiency
- Profiling-driven optimization
- Forecasting
- TCO analysis
Location
- San Francisco, CA
- New York City, NY
- Seattle, WA
Work Type
- Onsite only M-F
- Hybrid
Experience Level
- Senior
Education Level
- Bachelor's degree
Salary/Compensations
- $405,000—$485,000 USD
Benefits
- Competitive compensation
- Optional equity donation matching
- Generous vacation
- Generous parental leave
- Flexible working hours
About the Company
- Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society.
- The team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders.
- Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry.
- Anthropic is a public benefit corporation headquartered in San Francisco.
- We believe that the highest-impact AI research will be big science, working as a single cohesive team on large-scale research efforts.
- We value impact and advancing long-term goals of steerable, trustworthy AI.
- We view AI research as an empirical science.
- We are an extremely collaborative group, hosting frequent research discussions.
- Our research directions include GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Equal Opportunity
- We encourage you to apply even if you do not believe you meet every single qualification.
- We urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.
- We think AI systems like the ones we're building have enormous social and ethical implications, which makes representation even more important.
- We strive to include a range of diverse perspectives on our team.