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FluidStack

Builds and runs GPU clusters for AI labs

Product Engineer - Compute Operations

Software EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USAIn-person

About the Job

Requirements

  • You have shipped production code in Go, Python, or TypeScript, and can learn other languages as the problem requires.
  • You have built production features using large language model APIs, Model Context Protocol servers, and agentic frameworks.
  • You use AI coding tools such as Claude Code and Cursor and can have agents perform useful work autonomously.
  • You can identify problems, design solutions, and ship them independently.
  • You have moved quickly under deadlines while leaving maintainable foundations for other engineers.
  • You have participated in an on-call rotation or worked alongside on-call teams, and have translated operational problems into systems that reduced pager noise.
  • You have demonstrated product judgment by shipping clear interfaces and workflows that reflect operational work.

Responsibilities

  • Build a fleet health system with real-time telemetry and tiered health checks across Kubernetes and bare metal, unified through an API, with alarms correlated into incidents and probable causes drafted for on-call teams.
  • Automate the repair and return-to-manufacturer-authorization workflow from failure detection through triage, parts, vendor return, and return to service; generate production engineers’ shift task lists and report return-to-service time.
  • Deliver hardware qualification software for burn-in, performance baselining, and hardware validation using rack-level workflows, with acceptance evidence attached to each machine’s record.
  • Operate facility maintenance and fleet systems together; own the asset model and migration, ensure asset registers are ready before external audits, and retire legacy datacenter inventory tools before new buildings are energized.
  • Convert standard operating procedures, training records, and technician qualifications into auditable structured data; build dashboards for site service-level objectives, deployment cycle time, and labor ramp.
  • Work on site and on rotation alongside production engineers and facility operators to build tools used in their next shift.

Desired Qualifications

  • Experience in production engineering or site reliability engineering on large graphics processing unit 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 supervisory control and data acquisition.
  • 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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