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Fluidstack is building civilization-scale AI compute infrastructure, acquiring power, designing and operating data centers, and rethinking every layer of the stack. The company's mission is to deploy frontier compute infrastructure faster than anyone else, ensuring AI expands human freedom rather than constrains it.
As a Product Engineer, AI, you will work on the Decision Team, which owns critical systems that automate and optimize Fluidstack's operations. You'll tackle some of the company's highest-leverage problems:
**Key Problem Areas:**
- Build the hiring machine as software: transform recruiting workflows, interview scheduling, and onboarding into an integrated system that removes manual bottlenecks.
- Build the cash view: create systems that derive near-term spend forecasts, turning purchase orders, contracts, and build milestones into order schedules, cash demand curves, and payment schedules that recompute as conditions change.
- Build the capital pipeline: automate the flow from approved budget through capital release to spending, gated on build milestones, with automatic proof chains for financing drawdowns.
- Parse contracts and obligations: extract terms, prices, deadlines, penalties, and SLAs from MSAs and change orders so delivery leads and finance teams have structured data and generated work.
- Embed forward-deployed systems: work alongside finance, treasury, accounting, legal, and people teams to turn approvals, contract terms, and reconciliations into structured data and automated workflows.
**How You'll Work:**
You'll operate with full autonomy, owning problems end-to-end without waiting for permission. The culture emphasizes insane urgency, first-principles reasoning, and building things that matter. You'll work at high intensity on the frontier of AI infrastructure.
**Requirements:**
- Shipped production code in Go, Python, or TypeScript; ability to pick up whatever language the problem demands.
- Built real features on LLM APIs (OpenAI, Anthropic, or open-weight models), MCP servers, and agentic frameworks.
- Daily work with AI coding tools like Claude Code and Cursor; experience getting agents to do useful autonomous work.
- Ability to identify problems, design solutions, and ship without waiting for direction or approval.
- Track record of moving fast under deadline while building foundations others can extend.
- Credibility with experts outside engineering (finance leads, lawyers, recruiters, auditors) and proven ability to drive adoption of software in their real workflows.
- Product taste demonstrated in shipped work: interfaces that are obvious to domain experts, workflows that match how work actually happens.
- Bonus skills: ERP and fixed asset accounting, FP&A, cash forecasting, capital planning, structured finance/treasury, contract lifecycle systems, ATS/HRIS integrations (Ashby, Greenhouse, Rippling, Workday), LLM extraction over legal/financial documents.
