Join Anthropic as a Data Center Engineer to enhance reliability and infrastructure management for AI systems.
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Last verified on the company career page 1 hour ago
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In this role, the Data Center Engineer focuses on managing power and cooling systems, ensuring efficient load management and reliability across data center operations. Key skills include expertise in power distribution, reliability modeling, and familiarity with telemetry and control systems. This position is ideal for experienced engineers with a strong background in data center infrastructure and a collaborative mindset, as they will work closely with various teams and external partners to enhance system performance.
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As an engineer on this team, you'll sit at the intersection of IT and facilities. You'll build the power models, availability models, topology and load management requirements that operate more efficiently against our physical envelope. Your work will directly shape which sites we lease, what SLAs we sign, how far we oversubscribe, and where workloads are placed.
Topology and load management. Own the power and cooling topology of our fleet as a living dataset, validate it and its telemetry against how the buildings really behave, and define how load management behaves under failure across chips and capacity providers, from requirements through commissioning and incident support.
Reliability modeling. Build and audit availability models of data center electrical and mechanical systems, define Cloud availability zones and failure domains, from a single site to the whole fleet.
Power modeling and load forecasting. Build models of power draw from chip to rack to facility, by workload and hardware generation, and use them to set capacity planning targets, design envelope, and load forecasting.
Partner diligence. Work with data center developers, operators, cloud providers and chip vendors to drive design improvements and hold them to SLA-grade performance, with technical diligence on their architectures, reliability studies, rack power specifications and operator interfaces.
Deep knowledge of data center power distribution and cooling architectures, redundancy schemes, and how they interact with IT load profiles.
Depth in at least one of: reliability engineering, power modeling and energy scheduling, or load management and controls (telemetry, IT/OT interfaces, load transfer and shedding systems).
Familiarity with SCADA/BMS/EPMS, telemetry pipelines, and control systems. Experience with software that bridges IT and OT.
Exposure to accelerator deployments and their power management interfaces, or to capacity overallocation in large compute fleets, strongly preferred.
Ability to translate between infrastructure engineering, software teams, legal and commercial teams, and external partners.
Bachelor's degree in Electrical Engineering, Mechanical Engineering, Power Systems, Reliability Engineering, Controls Engineering, or a related field
5+ years of experience in data center infrastructure, facility engineering, or reliability engineering
Demonstrated experience with data center power distribution and cooling system architectures, and infrastructure failure mode management
Demonstrated experience in at least one of the following:
Building quantitative reliability or availability models (Monte Carlo, fault tree, reliability block diagram, or FMEA)
Building power, energy or capacity models and forecasts from measured data
Building, testing or operating software-based power management, load shedding, or control systems
Track record of cross-functional collaboration across hardware, software, and facilities teams
Experience in more than one of the three focus areas above
Experience with accelerator-class deployments, rack power architectures, and their power management interfaces
Experience with integrated systems testing and commissioning (L4/L5), or writing sequences of operation
Experience with SLA development, availability commitments, or service credit frameworks in leases or cloud contracts
Experience with energy storage, microgrid integration, demand response, or behind-the-meter generation
Exposure to ML or optimization techniques applied to infrastructure or energy systems
The annual compensation range for this role is listed below.
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