Anthropic· Compute· Remote-Friendly, United States
Data Center Engineer, Resource Efficiency – Compute Supply
Classified Tasks (10)
Automate 0%Augment 70%Human-Only 30%
Augment (7)
AI assists, human decides
Build systems, models, and control loops to optimize allocation and consumption of power, cooling, and physical capacity across the TPU/GPU fleet
technical
Build models that forecast consumption across electrical and mechanical subsystems
analytical
Perform statistical modeling of cluster utilization, workload profiles, and failure modes
analytical
Use forecasting models to inform capacity planning, energy procurement, and oversubscription targets and risks
operational
Design IT/OT interfaces that bridge compute orchestration with facility controls to enable real-time telemetry across accelerator hardware, power distribution, cooling, and schedulers
technical
Build and operate load management systems that leverage power and cooling topology for power/thermal-aware placement to maximize throughput while meeting SLOs
technical
Provide technical diligence on partner architectures
technical
Human-Only (3)
Requires human judgment
Own the technical strategy for converting raw data center capacity into reliable, efficient compute
leadership
Coordinate across power topology, workload scheduling, and real-time telemetry to push utilization toward the physical envelope while maintaining availability commitments
operational
Partner with data center providers to drive design optimizations and enforce SLA-grade performance standards
communication
Job description
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's AI infrastructure operates at massive scale, and extracting maximum compute throughput from every watt is a first-order priority. As a Power & Resource Efficiency Engineer, you'll sit at the intersection of IT and facilities — building the systems, models, and control loops that optimize how we allocate and consume power, cooling, and physical capacity across our TPU/GPU fleet. You'll own the technical strategy for turning raw data center capacity into reliable, efficient compute, working across power topology, workload scheduling, and real-time telemetry to push utilization as close to the physical envelope as possible while maintaining our availability commitments. What You'll Do Build models that forecast consumption across electrical and mechanical subsystems, informing capacity planning, energy procurement, oversubscription targets and risks, including statistical modeling of cluster utilization, workload profiles, and failure modes. Design IT/OT interfaces that bridge compute orchestration with facility controls, enabling real-time telemetry across accelerator hardware, power distribution, cooling, and schedulers. Build and operate load management systems that use power and cooling topology to enable load management and power/thermal-aware placement to maximize throughput while meeting SLOs. Partner with data center providers to drive design optimizations and hold them accountable to SLA-grade performance standards, providing technical diligence on partner architectures. What We're Looking For Deep knowledge of data center power distribution and cooling architectures, and how they interact with IT load profiles. Experience with reliability engineering, SLA development, and failure-mode analysis. Proficiency in statistical modeling and simulation for infrastructure capacity or power utilization. Familiarity with SCADA/BMS/EPMS, telemetry pipelines, and control systems. Experience building software that bridges IT and OT. Exposure to accelerator deployments and their power management interfaces strongly preferred. Demand response, grid interaction, or behind-the-meter generation experience is a plus. Ability to translate between infrastructure engineering, software teams, and external partners. Required Qualifications Bachelor's degree in Electrical Engineering, Mechanical Engineering, Power Systems, Controls Engineering, or a related field 5+ years of experience in data center infrastructure or facility engineering Demonstrated experience with data center power distribution and cooling system architectures Experience building or operating software-based power management, load scheduling, or control systems Proficiency in Python or similar languages for statistical modeling, simulation, or automation of data center infrastructure optimizations Familiarity with SCADA, BMS, EPMS, or industrial control systems and associated protocols (Modbus, BACnet, SNMP) Track record of cross-functional collaboration across hardware, software, and facilities teams Preferred Qualifications Master's or PhD in Contr