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FluidStack

Builds and runs GPU clusters for AI labs

Decision Engineer, Compute Operations

AI Application Engineering +3Confirmed live in the last 24 hours
Full-timeIn-person
Earn $5k if you accept an offer

About the Job

Requirements

  • You have shipped production code in Go, Python, or TypeScript, and can learn whichever language the problem requires.
  • You have built production features using large language model APIs, including OpenAI, Anthropic, or open-weight models, MCP servers, and agentic frameworks.
  • You work daily with AI coding tools such as Claude Code and Cursor, and use agents autonomously to complete useful work.
  • You identify problems, design solutions, and ship them without waiting for direction or approval.
  • You have moved quickly under deadlines while building foundations that other engineers can extend.
  • You have participated in an on-call rotation or worked alongside on-call staff, and translated operational pain into systems that reduce pager noise.
  • You have demonstrated product judgment through interfaces and workflows that are clear to engineers on rotation and reflect how the work is performed.

Responsibilities

  • Build a fleet health system with real-time telemetry and tiered health checks across Kubernetes and bare metal, exposed through a shared API, with alarms correlated into incidents and probable causes drafted for on-call responders.
  • Create a tracked repair and return-material-authorization workflow from failure detection through triage, parts, vendor return, and service restoration; automate repair routing, generate production engineers' shift task lists, and report time to return to service.
  • Develop rack-level software workflows for burn-in, performance baselining, and hardware validation so accelerators can be brought online repeatably with acceptance evidence recorded for every machine.
  • Own the facility maintenance system for lockout/tagout and work orders, its rollout to additional sites, asset-register readiness, migration, and retirement of legacy datacenter inventory ahead of new facility activation.
  • Convert standard operating procedures, training records, and technician qualifications into auditable structured data; report site service-level objectives, deployment cycle time, and labor ramp on customer-requested dashboards.
  • Work on site and on the on-call rotation alongside production engineers and facility operators, building systems for their operational use.

Desired Qualifications

  • Production engineering or site reliability engineering on large GPU fleets.
  • Experience with hardware qualification or burn-in frameworks.
  • Experience with baseboard management controller, Redfish, or IPMI tooling.
  • Experience with computerized maintenance management systems, data center infrastructure management, or asset management systems.
  • Experience with building management systems, electrical power monitoring systems, or SCADA.
  • Experience with Prometheus and Grafana.

About the Company

FluidStack

Builds and runs GPU clusters for AI labs

Fluidstack provides large clusters of GPU servers to AI labs training advanced models, and it builds custom data centers for customers that outgrow existing facilities. In 2025, Anthropic chose Fluidstack to build data centers in Texas and New York as part of a $50 billion investment in American AI infrastructure. Labs pay for dedicated clusters of Nvidia GPUs, sometimes tens of thousands of chips, housed in partner data centers around the world. They reach the clusters through a web console or API, while Fluidstack runs the hardware, networking, and day-to-day operations. Fluidstack was founded in London in 2017 and has its headquarters in New York.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$12.4B
Headquarters
New York City, New York
Founded
2017

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