Decision Engineer, Infrastructure Development & Delivery

Fluidstack

• $130K — $155K *
Real Estate & Construction
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of software engineering experience in Go, Python, and TypeScript
  • Proficient in full-stack web development frameworks like React or Next.js
  • Hands-on with LLM APIs and creating MCP servers
  • In-depth knowledge of AI coding agent tools and agent frameworks
  • Ability to work autonomously and deliver high-impact results
  • Strong design sense, important for building low-barrier applications
  • Solid systems thinking to create scalable, maintainable solutions
  • Excellent communication for bridging technical and non-technical discussions

Responsibilities

  • Build internal tools and AI applications to increase productivity across teams
  • Design and maintain shared AI infrastructure for organizational use
  • Integrate new AI capabilities into existing products and tools
  • Develop custom integrations between LLMs and company systems
  • Stay updated on AI advancements and explore new applications
  • Document processes to support team training on new tools

Benefits

  • Competitive total compensation package including cash and equity
  • Health, dental, and vision insurance
  • Retirement plan
  • Generous PTO policy
Full Job Description
How We Operate
  • Be a barrel. Full autonomy. Own things end to end, take on scope without being asked, no permission required to operate outside your core role.
  • Insane urgency. We drive everything forward as fast as possible.
  • Reason from 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.
  • Build something that actually matters. If you're going to spend your time, spend it on something that matters to the world.


The Decision Team

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.
Role Scope
  • Build the schedule that runs the portfolio: one template schedule per building type, instantiated per project, with every activity tied to the materials it consumes, so need-by dates for switchgear, transformers, and cooling fall out of the critical path instead of a spreadsheet, and a slip in permitting reprices the procurement calendar the same hour.
  • Turn the site into structured data: work packages, contractor field entries, rack placements, cable runs, and QA inspections land as records tied to the design revision they were built against, percent complete is computed from evidence rather than reported on a call, and the customer sees delivered against committed without anyone assembling a deck.
  • Ship change orders as a workflow, not an email chain: scope, cost, and schedule impact drafted from the design delta, routed through legal, finance, and the general contractor with the approval trail attached, and the bill of materials and schedule updated the moment the order is signed.
  • Make the design the source of truth: ingest building information models straight into the bill of materials with a reviewable diff on every revision, generate submittal requirements per spec section, and keep sites, buildings, and data halls as one canonical record that every downstream system reads instead of copies.
  • Ship commissioning as software: test procedures generated per asset from the design revision across all five levels, results landing as evidence against the asset they tested, energization gates that check themselves, and handover that opens on proof instead of a signature.
What We're Looking For

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 pick up whatever language the problem demands.
  • You've built real features on LLM APIs (OpenAI, Anthropic, or open-weight models), MCP servers, and agentic frameworks.
  • You work daily with AI coding tools like Claude Code and Cursor, and you get agents doing useful work autonomously alongside you.
  • You identify problems, design the solution, and ship it without waiting for direction or approval.
  • You've moved fast under deadline while leaving foundations that other engineers extended after you moved on.
  • You've earned credibility with people who build physical things: construction leads, field engineers, schedulers, or commissioning agents, and driven adoption of your software inside their real deadlines.
  • Your product taste shows in what you've shipped: interfaces field crews call obvious, and workflows that match how the work actually happens.
  • Bonus: Construction tech or project controls (P6, schedule engines, critical path). BIM, IFC, or Revit data models. Commissioning, BMS/EPMS, or controls protocols. Document control and submittal workflows. Graph data models. Computer vision on site imagery.


Benefits:
  • Competitive total compensation package (cash + equity)
  • Health, dental, and vision insurance
  • Retirement plan
  • Generous PTO policy


We are committed to pay equity and transparency.

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