Product Engineer, Infrastructure Deployment

Posted An Hour Ago
Be an Early Applicant
San Francisco, CA, USA
In-Office
150K-350K Annually
Mid level
Artificial Intelligence • Software
The Role
Build software to automate and accelerate data-center deployment: a live deployment knowledge graph, sequencing and scheduling rules, contractor bidding workflows, per-rack checklists and inspections, and automated closeout evidence. Collaborate with field engineers to turn site data into structured, queryable systems and tools that reduce manual work and speed handover to operations.
Summary Generated by Built In
About Fluidstack

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!

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 deployment knowledge graph, forward-deployed on live sites beside the Infrastructure Deployment Engineers, so every rack, cable run, fiber link, QA inspection, OTDR trace, optical loss result, and copper certification lands as structured data tied to the exact link it tested, and as-builts become a live, queryable model of what was actually built.

  • Encode the real sequencing rules of a site bring-up (the network room comes up first, the end-of-row rack is the synchronization point) so software generates the low voltage contractor schedule, milestone tracking, site access, and material staging, replans when a shipment slips, and flags the delay before it costs the date.

  • Turn the contractor bidding workflow into software: vendor bids in, a selected contract out, and every vendor ranked by measured speed and QA accuracy per region, so the next award is made on performance data the graph already holds.

  • Generate per-rack checklists and multi-stage inspection plans straight from design documentation, verify submitted results against spec automatically, and auto-create the punch list, so deployment engineers spend their time adjudicating exceptions.

  • Assemble closeout the moment work completes: final test reports, as-builts, and root cause analyses produced from the graph, so handover to operations is a state transition with evidence attached and an ops tech can localize a down link (transceiver versus cable versus DWDM) with zero training.

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 requires.

  • You've built with LLM APIs (OpenAI, Anthropic, or open-weight models), created and consumed MCP servers, and shipped with agentic frameworks.

  • You work with AI coding tools like Claude Code and Cursor every day and get agents producing real work autonomously alongside you.

  • You've spotted a problem no one assigned you, designed the fix, and shipped it to production with minimal direction.

  • You've moved fast without leaving wreckage: systems you built under deadline are ones other engineers extended rather than rewrote.

  • You've earned credibility with people who don't live in software, field engineers or cabling crews, and driven adoption of your tool on their turf.

  • You sweat product and design details, and the tools you've shipped are ones users chose over their spreadsheets.

  • Bonus: Structured cabling and fiber (OTDR, optical loss testing). Rack and cluster bring-up. IP provisioning. DCIM tooling. Time on a deployment site.

Compensation & Benefits

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.

 
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.

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 consumed MCP servers and shipped with agentic frameworks
  • Use AI coding tools like Claude Code and Cursor and run agentic workflows autonomously
  • Designed and shipped fixes to production with minimal direction
  • Built systems that others extended rather than rewrote (maintainable under deadline)
  • Earned credibility with field engineers or cabling crews and driven adoption of tools on-site
  • Strong product and design focus; shipped tools users prefer over spreadsheets
  • Structured cabling and fiber (OTDR, optical loss testing)
  • Rack and cluster bring-up experience
  • IP provisioning experience
  • Experience with DCIM tooling
  • Time on a deployment site (on-site deployment experience)
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The Company
HQ: London
30 Employees
Year Founded: 2017

What We Do

Instantly reserve dedicated clusters of NVIDIA H200s and GB200s for any scale to supercharge your training and inference workflows.

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