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FluidStack

Builds and runs GPU clusters for AI labs

Software Engineer - Facilities

Backend EngineeringConfirmed live in the last 24 hours
Full-time$224k - $264k /yrIn-person

About the Job

Requirements

  • Experience building large-scale software systems, particularly systems that produce and process large volumes of data, is relevant.
  • Production coding experience in Go, Python, or TypeScript, with ability to learn and use other languages as needed.
  • Experience with high-throughput messaging systems such as NATS or Kafka, including ordering, delivery guarantees, backpressure, and concurrency-versus-correctness tradeoffs.
  • Experience designing data models for large volumes of timestamped data and reasoning about slow queries, write throughput, query performance, retention, and schema evolution.
  • Experience instrumenting production services with metrics, logs, and profiling, and using instrumentation to find bottlenecks or explain incidents.
  • Ability to explain design alternatives, selection rationale, and when a design was changed because it no longer fit the problem.
  • Ability to define interfaces and failure boundaries, account for unavailable dependencies, and test failures and recovery paths.
  • Experience tracing data from source through services and storage, accounting for missing, duplicate, late, and invalid data, and distinguishing stale values from incorrect values.

Responsibilities

  • Build and own services used by other teams, including device integrations, telemetry pipelines, equipment models, and APIs across sites.
  • Design messaging and state layers that preserve ordering where needed, handle slow consumers, and recover from restarts without data loss or duplicate actions.
  • Own data contracts and engineering standards, making device identity, units, timestamps, and data quality explicit, and evolving schemas and APIs without breaking consumers.
  • Build the path from control requests to confirmed results by enforcing authorization, deadlines, and equipment constraints, tracking state changes, and making retries safe.
  • Build observability for failures by measuring ingestion lag, dropped data, stale readings, query latency, and command completion.
  • Prove system behavior with unit tests, integration tests, and simulated devices that exercise failures and recovery before changes reach live equipment.

Desired Qualifications

  • Prior datacenter or controls experience.
  • Experience with Go, NATS, Redis, ClickHouse, Protobuf/gRPC, Kubernetes, ArgoCD, Prometheus, or Grafana.
  • Experience with industrial protocols such as Modbus or OPC UA.

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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