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!
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.
Build one capital pipeline from approved budget to released capital to spent dollar, gated on build milestones the delivery system already verifies, so releasing nine figures takes a day of judgment backed by evidence the system has assembled.
Assemble the proof chain behind every financing drawdown automatically: what was ordered, built, energized, and accepted, so the cost of capital reflects our data quality and funding follows construction within days.
Parse every MSA, change order, and side letter into obligations, prices, deadlines, and penalties that flag the SLA breach or price escalation in time to act, and let the corpus of executed deals price and redline the next negotiation.
Build the continuous close: each asset tracked from purchase through construction-in-progress to in-service, capitalization and depreciation posting as events the moment they happen, so the close becomes a query over books that never drifted.
Embed forward-deployed with finance, treasury, accounting, and legal teams, turning their forecasts, approvals, contract terms, and reconciliations into structured data and generating the models, checklists, and reviews that send their judgment to the hard calls.
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 work in whatever language the problem needs, moving primarily with AI coding tools.
You've built with LLM APIs (OpenAI, Anthropic, or open-weight models), created and used MCP servers, and worked with agentic frameworks.
You use Claude Code, Cursor, or similar tools daily and get agents working autonomously alongside you.
You've found a problem no one assigned you, designed the fix, and shipped the result end to end without waiting for approval or handing work off.
You've moved fast without boxing the team in: engineers who came after you built on your foundations instead of rewriting them.
You've earned credibility with experts outside engineering: finance leads, lawyers, or auditors, and driven adoption of your software inside their real deadlines, like a working close calendar.
You've owned the product and design decisions on things you shipped, and users can tell: as the barrier to building drops, taste matters more.
Bonus: ERP and fixed asset accounting. FP&A and capital planning. Structured finance or treasury operations. Contract lifecycle systems. LLM extraction over legal and financial documents.
Our cash compensation range for this role is $150,000-$275,000. Final offers may vary from the amount listed based on geography, candidate experience and expertise, relevant licenses/credentials, and other factors. We welcome compensation discussions if this range doesn't meet your requirements. Outstanding candidates may be eligible for adjusted terms, plus meaningful equity that ensures you benefit directly from the company's long-term performance.
To provide greater transparency to candidates, we share base pay ranges for all US-based job postings. Our compensation package includes base salary, equity for all full time roles, benefits, and, for applicable roles, commissions plans.
Competitive total compensation package (cash + equity)
Health, dental, and vision insurance
Retirement plan
Generous PTO policy
We are committed to pay equity and transparency.
We are committed to pay equity and transparency.
Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email [email protected] with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.
Skills Required
- Shipped production code in Go, Python, or TypeScript
- Built with LLM APIs (OpenAI, Anthropic, or open-weight models)
- Created and used MCP servers
- Worked with agentic frameworks
- Use Claude Code, Cursor, or similar tools daily and get agents working autonomously
- Identified problems autonomously and shipped end-to-end solutions
- Built foundations that other engineers can extend without rewriting
- Earned credibility with finance, legal, or audit partners and driven software adoption
- Owned product and design decisions for shipped work
- Experience with ERP, fixed asset accounting, FP&A, structured finance, treasury, or contract lifecycle systems
- Experience applying LLM extraction to legal and financial documents
What We Do
Instantly reserve dedicated clusters of NVIDIA H200s and GB200s for any scale to supercharge your training and inference workflows.








