# Data Center Engineer, Resource Efficiency – Compute Supply

**Company**: Anthropic
**Location**: Remote-Friendly, United States
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $320,000-$405,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/5159642008
**Canonical**: https://yubhub.co/jobs/job_e53014e6-57c

## Description

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.

Key responsibilities include:

- Building 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.

- Designing IT/OT interfaces that bridge compute orchestration with facility controls, enabling real-time telemetry across accelerator hardware, power distribution, cooling, and schedulers.

- Building and operating load management systems that use power and cooling topology to enable load management and power/thermal-aware placement to maximize throughput while meeting SLOs.

- Partnering with data center providers to drive design optimizations and hold them accountable to SLA-grade performance standards, providing technical diligence on partner architectures.

In this role, you'll need to have 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 is also essential.

Additionally, proficiency in statistical modeling and simulation for infrastructure capacity or power utilization, familiarity with SCADA/BMS/EPMS, telemetry pipelines, and control systems, and exposure to accelerator deployments and their power management interfaces are highly desirable.

This is a challenging and rewarding role that requires a unique blend of technical expertise, business acumen, and collaboration skills. If you're passionate about data center infrastructure, AI, and sustainability, we encourage you to apply.

## Skills

### Required
- data center power distribution and cooling architectures
- _SYSTEMS
- reliability engineering
- SLA development
- failure-mode analysis
- statistical modeling and simulation
- SCADA/BMS/EPMS
- telemetry pipelines
- control systems
- accelerator deployments
- power management interfaces

### Nice to have
- Python
- similar languages
- control theory
- dynamical systems
- cyber-physical systems design
- energy storage
- microgrid integration
- demand response
- behind-the-meter generation