Data Center Engineer, Reliability & Infrastructure Management – Compute Supply

Anthropic; San Francisco (CA); Hybrid; USD 320,000 - 405,000; Full time

Job summary

Anthropic seeks an engineer bridging IT and facilities to model power, topology, and load for our data-center fleet. You’ll define availability and capacity targets, work with operators and vendors, and shape where workloads are placed across sites in a fast-growing AI research environment.

Deep expertise in data center power distribution, reliability modeling, and energy scheduling is essential, with strong collaboration across hardware, software, and facilities teams to meet SLA-grade

Qualifications

• Bachelor's degree in a field relevant to data center infrastructure or engineering.
• 5+ years of experience in data center infrastructure, facility engineering, or reliability engineering.
• Experience with data center power distribution and cooling system architectures and failure mode management.
• Experience in at least one: building reliability/availability models, building power/energy models, or software-based power management.
• Track record of cross-functional collaboration across hardware, software, and facilities teams.

Responsibilities

• Own power and cooling topology for data centers and validate telemetry against real-world behavior.
• Build and audit availability models for data center electrical and mechanical systems; define Cloud availability zones and failure domains.
• Develop power draw models from chip to facility to support capacity planning, envelope design, and load forecasting.
• Collaborate with data center developers, operators, cloud providers, and vendors to drive design improvements and SLA-grade performance.

Skills

Power modeling

Reliability engineering

SCADA/BMS/EPMS

Telemetry pipelines

Cross-functional collaboration

Education

Bachelor's degree in Electrical/Mechanical/Power Systems

Tools

SCADA

EPMS

Telemetry

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

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.

What You'll Do

• 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.

What We're Looking For

• 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.

Required Qualifications

• 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

Preferred Qualifications

• 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

Annual Salary

$320,000-$405,000 USD

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so 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. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

How We're Different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Guidance on Candidates' AI Usage:

Learn about our policy for using AI in our application process.