• Hold the company's view of where data center infrastructure is going.
• Track vendor and hyperscaler roadmaps, research, standards work, and the startup and venture landscape across power and energy, cooling and thermal, construction and delivery, rack and hall architecture, siting and regulation, and the economics that connect them. Right now that means questions like whether facility-level 800 VDC becomes the standard, how far liquid cooling has to go as racks move from roughly 200 kW toward a megawatt, how much of a build program can be moved into a factory, and whether behind-the-meter generation beats waiting in the interconnect queue. Those specific questions will have changed within a year, holding the current version of them is the job.
• Formulate and validate the product and engineering thesis. Turn that view into a defensible position on what we build, buy, or partner for, pressure-tested against cost, schedule, and what the physical plant can actually support — and say so plainly when the evidence does not hold up.
• Own the technical reference view of a hall at each GPU generation: density, power envelope, cooling topology, and what our operating and prospective sites can and cannot absorb. This includes getting on site to see them.

Influence the numbers finance, pricing, and sales depend on: cost per rack, per MW, and per GPU-hour, and how they move with density, cooling approach, and silicon mix. Be able to defend them under challenge.

Make the work land commercially. Support sales and delivery in technically demanding customer and partner conversations, feed product and go-to-market with what we can credibly offer and when, and provide technical diligence on infrastructure partners, colocation providers, vendor reference designs, and prospective tuck-in targets.

Required Qualifications

• Hands-on experience designing, building, or operating data center infrastructure at scale,
• Demonstrated experience with GPU-based compute environments, and
• Working command of the power side of the business, interconnect, capacity procurement, and the constraints that actually govern build timelines

Preferred Qualifications

• Fluency with the landscape you would be scanning: who the vendors, hyperscalers, standards bodies, utilities, and startups are in data center power and cooling, and a view on which of them matter. Expect to be asked what you think is currently overhyped, and why.
• Demonstrated ability to do research in the applied sense: taking an open question, investigating it from primary sources — vendor roadmaps, standards documents, utility filings, academic literature, your own benchmarking — and producing a defensible position under genuine uncertainty. A PhD in a relevant technical field is one good route to this and is valued here; sustained industry research, standards-body work, or a body of internal technical assessments that changed real decisions are equally valid. Either way, the role turns on the second half: translating that work for engineering, product, go-to-market, and finance, because it informs all four .
• Significant hands-on experience designing, building, operating, or engineering data center infrastructure.
• Strong understanding of data center architecture and physical infrastructure.
• Demonstrated experience with GPU-based compute environments.
• Working knowledge of the power side of the business: utility interconnect, capacity procurement, PPAs, backup generation, and the lead times that govern each.
• Experience building or stress-testing infrastructure cost models, and comfort defending those numbers to finance and commercial stakeholders.
• Deep understanding of power, cooling, rack design, density, electrical/mechanical infrastructure, and related data center considerations.
• Experience evaluating data center infrastructure, sites, or large-scale compute environments.
• Ability to understand emerging technologies and assess their practical implications for infrastructure.
• Strong technical communication and the ability to influence engineering and business stakeholders.
• Comfortable operating as a horizontal subject-matter expert rather than owning a traditional operational team.
• Comfortable operating as an individual contributor with high ownership in a lean, early-stage team.

• Experience across multiple data center builds and multiple vendor reference designs.
• Background in liquid cooling (direct-to-chip or immersion) or high-density rack deployments — meaningful above 100 kW, and increasingly relevant at the 200 kW-plus densities current GPU racks now draw.
• Experience with commissioning, capacity planning, or handover of new data center halls into production.
• Publications, patents, standards-body participation, or a visible external presence in the data center or infrastructure community.
• Spent your education and career working deeply in data center architecture, but you have the foundational knowledge and intellectual curiosity to quickly understand new architectures and technologies as they emerge.

Location

• Hybrid role based in downtown Bellevue, WA.
• Approximately three days per week in the office.
• Candidates elsewhere in the U.S. who are open to relocation are encouraged to apply.
• U.S. work authorization is required. Visa sponsorship is not currently available.
• Export control: this role involves technologies subject to U.S. export control regulations. Candidate eligibility may be subject to export control screening and, where applicable, licensing.
• Travel : Willingness and ability to travel as needed internationally to data centers and co-locations (up to 25%)

Why Join?

• High-impact technical role: Directly influence the technology direction of an organization building AI infrastructure at scale.
• Ground-floor opportunity: Help establish technical strategy, architecture, processes, and culture within a growing organization.
• High ownership: Operate as a senior individual contributor with substantial autonomy and direct access to senior technical leadership.
• Cross-disciplinary exposure: Work across AI models, inference, accelerators, software systems, networking, infrastructure, and economics.
• Cutting-edge technical problems: Work on multi-accelerator inference, intelligent routing, performance optimization, token economics, and compiler, kernel, and runtime technologies.
• Research with practical impact: Turn emerging research and technology developments into decisions that directly affect engineering, product, commercial strategy, and investment.
• Lean, senior environment: Work with a small group of highly experienced technical contributors rather than within a large management hierarchy.