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FluidStack

Builds and runs GPU clusters for AI labs

Product Engineer - Business Operations

AI Application EngineeringUpdated on Oct 29
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • You have shipped production code in Go, Python, or TypeScript, and can learn other languages as the problem demands.
  • 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 can use agents autonomously alongside you.
  • You can identify problems, design solutions, and ship them independently.
  • You have moved quickly under deadlines while leaving foundations that other engineers could extend.
  • You have earned credibility with experts outside engineering, such as finance leads, lawyers, recruiters, or auditors, and driven adoption of software within their real deadlines.
  • You have demonstrated product judgment through shipped interfaces and workflows that users find intuitive and that match how their work happens.

Responsibilities

  • Build the recruiting system, syncing hiring data in both directions, making interviewer supply and workload visible to hiring managers, and generating onboarding when an offer is signed.
  • Build a cash-view system that converts purchase orders, contract terms, and construction milestones into an order schedule, monthly cash-demand curve, and payment schedule that update as procurement and construction change.
  • Build a capital pipeline from approved budget through released capital to expenditure, gated by verified build milestones, and automatically assemble the supporting proof chain for financing drawdowns.
  • Parse master service agreements, change orders, and side letters into obligations, prices, deadlines, penalties, and service-level agreements, and make those terms available to delivery, legal, and finance workflows.
  • Embed with finance, treasury, accounting, legal, and people teams through closes, drawdowns, negotiations, and hiring loops, converting approvals, contract terms, screens, and reconciliations into structured data and generated work.
  • Develop a continuous-close workflow in which capitalization and depreciation post as events occur.

Desired Qualifications

  • Experience with enterprise resource planning systems and fixed-asset accounting.
  • Experience with financial planning and analysis, cash forecasting, and capital planning.
  • Experience with structured finance or treasury operations.
  • Experience with contract lifecycle systems.
  • Experience integrating applicant tracking systems and human resource information systems, such as Ashby, Greenhouse, Rippling, or Workday.
  • Experience with large language model extraction from legal and financial documents.

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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