How We Operate- High ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.
- Velocity. We drive everything forward as fast as possible.
- First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.
- Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.
The Software Engineering TeamExamples of key exciting problems the team is working on:- We're building the pipeline that processes thousand-page vendor unstructured material against our own DC design to automate the generation of an end to end site design and schedule.
- We're building the live model of a AI infrastructure project's entire delivery schedule, durable workflows handing off across every team, to replace static Gantt charts with a plan that updates itself as reality changes.
- We're building the agent platform that wraps AI in real authorization, audit, and guardrails, to let agents accelerate the development of infrastructure instead of just advising report on it.
Role Scope- Build core primitives end to end. Entity ownership, audit, authorization, orchestration. You make the right thing the default and the wrong thing hard.
- Own the domain model. Turn Fluidstack's world of power, datacenters, and chips into composable entities that still hold up years from now.
- Define interactions with the outside. Interface with vendor systems and ingest the formats our domain actually speaks: KMZ, BIM, Revit, vendor docs.
- Make AI agents first-class operators of our systems. Give them the tools, guardrails, and audit trails to act safely, not just advise.
What We're Looking ForThe 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 move toward ambiguity, not away from it. You walk into the fog, build the map, and explain it to everyone else.
- You learn at a steep slope. You reach real competence in an unfamiliar domain fast, whether it's a workflow engine, an authz model, or a geospatial format. We value this over existing expertise.
- You have taste in abstraction. You see the one primitive hiding under five janky one-offs, and you know when not to abstract.
- You model domains with rigor earned the hard way. You've gotten it wrong, felt the pain, and never forgot it.
- You pull structure out of mess. You've done real work turning messy, unstructured data into something usable, in ML, data engineering, or research.
- You're fluent with AI tooling. LLM APIs, MCP servers, and agentic frameworks, and you drive Claude Code, Cursor, or similar every day.
- You've shipped production code that other people depend on, and you're comfortable in any language using AI coding tools.
- Bonus: MLE work, especially extraction and synthesis from unstructured data. Workflow and orchestration engines (Temporal, Cadence, Airflow). Geospatial (KMZ/GIS) or BIM (Revit, IFC). Authorization and policy engines (OPA, Zanzibar-style, RBAC/ABAC). Audit or event-sourcing systems. Go, TypeScript, and Postgres.
Salary & Benefits- Competitive total compensation package (salary + equity).
- Retirement or pension plan, in line with local norms.
- Health, dental, and vision insurance.
- Generous PTO policy, in line with local norms.
The base salary range for this position is $150,000 - $250,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.
We are committed to pay equity and transparency.
