Controls Systems Engineer, Deployment Engineering

Controls Systems Engineer, Deployment Engineering LocationAustin, TX; New York, NY; San Francisco, CA; Seattle, WAEmployment TypeFull timeLocation TypeHybridDepartmentDeliveryCompensation$161K – $197KTo provide greater transparency to candidates, we share base pay ranges for all US-based job postings. Our compensation package includes base salary, equity for all full time roles, benefits, and, for applicable roles, commissions plans.This range reflects a good-faith estimate based on the applicable pay scale, the range previously established for this role, the compensation of individuals currently in equivalent positions, and/or the budgeted amount for the position. Actual compensation may vary based on experience, qualifications, and other factors.We welcome compensation discussions if this range doesn't meet your requirements. Outstanding candidates may be eligible for adjusted terms, plus meaningful equity that ensures you benefit directly from the company's long-term performance.Total compensation may also include equity in the form of restricted stock units. About FluidstackWe exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it. We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.We hire people who care deeply about this problem space. If that is you, please apply!How We OperateExtreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.Velocity. We drive everything forward as fast as possible.First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.The Deployment Engineering TeamExamples of key problems the team is working onTurn 10s to 100s of GWs of design into built, running infrastructure. The Design team sets the blueprint. This team is where it survives contact with a live construction schedule and becomes a real site.Close the gap between engineering-complete and operations-ready. A design that passes review still has to survive commissioning, integration, and energization, and that gap is where deployment work lives.Make the tenth site faster and cleaner than the first. Every deployment feeds field learnings back into the standards, so a one-off fight at one site becomes a repeatable playbook at the next.Hand off infrastructure that's reliable from the moment it goes live. AI compute workloads don't tolerate a shaky handover, so what this team commissions has to run right the day operations takes over.Role ScopeDeploy and commission BMS, SCADA, and EPMS systems at data center sites, running FAT, field integration, loop checks, sequence verification, and acceptance testing through to live handover.Support operational reliability of deployed control systems, responding to alerts and failures on live infrastructure and implementing fixes that prevent recurrence.Resolve field integration issues between control system layers and connected mechanical and electrical systems during commissioning, escalating with a clear problem description and proposed fix.Configure and verify control sequences, alarm setpoints, and...