# Decision Engineer, Compute Operations at FluidStack > Onsite · United States · Unspecified · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Afluidstack%3A1fa894eb-09ce-478f-b440-aae45aa4953e (read 2026-11-04). ## Facts (observed) - Company: [FluidStack](https://alderhq.app/companies/fluidstack) - Location text: New York, NY; San Francisco, CA; Austin, TX; Seattle, WA - Where it can be done from (inferred): Onsite · United States (evidence: "Location: New York, NY; San Francisco, CA; Austin, TX; Seattle, WA") - Posted: 2026-09-10 (55 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/fluidstack/1fa894eb-09ce-478f-b440-aae45aa4953e - Skills listed (inferred): TypeScript, Python, Go ## Pay and sponsorship - Posted pay: $224k–$300k per year (from the listing's pay field) - Market band for similar posted roles (New York, n 357): p25 $140k, median $175k, p75 $222k - H-1B filings at this company for similar roles, FY26: 4, median offered wage $275k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance)) - Licensed UK sponsor: registered as "Fluidstack Ltd" (checked 2026-11-03, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers)) ## Description (the employer's text) ### About Fluidstack We 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 Operate Be a barrel. Full autonomy. Own things end to end, take on scope without being asked, no permission required to operate outside your core role. Insane urgency. We drive everything forward as fast as possible. Reason from 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. Build something that actually matters. If you're going to spend your time, spend it on something that matters to the world. ### The Decision Team ### Examples of key problems the team is working on Automate the delivery of gigawatts. Every process that takes AI infrastructure from land to live compute becomes software: schedules, decisions, and todos generated from a live knowledge graph instead of chased by hand. Forward-deploy beside the experts. Product teams sit with quality managers, sourcing leads, and deployment engineers on factory floors and sites, and turn their judgment into systems that reach every unit. Deliver every supercomputer faster than the last. Dozens of concurrent projects feed one graph, so every lesson learned at one site becomes a preventive check at all of them. ### Role Scope Build incident management for physical assets: related alarms roll up into a single incident that reaches on-call with a probable cause already drafted, so work goes out the moment an alert lands. Root cause analysis traces every failure to the asset behind it, and on-call rotations run from the same system. Close the loop from failure to return to service: failure thresholds route machines to repair automatically. Each one is triaged, a spare is pulled from the warehouse and scanned at the swap, and the broken part goes back to the vendor on an RMA. Sequence and staff every job: each job runs as ordered steps, and the system checks one step is done before the next starts. Shift scheduling finds who is available, and each production engineer's shift todo list is automatically generated for them. Run the facility on a unified system: one asset register covers every piece of equipment across IT and facilities, and the CMMS schedules preventive maintenance, issues work orders, and runs lockout tagout. Roll it out from one live site to every site, retiring the legacy DCIM tooling on the way. Build tools anyone in front of a rack can use: operator tooling simple enough that anyone off the street knows exactly what to do. Scan this part of the rack, in this order, and the tool spots any mistakes. Every runbook becomes a guided, verified workflow. ### What We're Looking For The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would. You've shipped production code in Go, Python, or TypeScript, and you pick up whatever language the problem demands. You identify problems, design the solution, and ship it without waiting for direction or approval. You've moved fast under deadline while leaving foundations that other engineers extended after you moved on. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Afluidstack%3A1fa894eb-09ce-478f-b440-aae45aa4953e and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.