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FluidstackFluidstackSan Francisco, CA

Product Engineer, Infrastructure Deployment

Build and ship a live deployment knowledge graph and agentic software systems that automate AI supercomputer site bring-up, contractor workflows, QA inspections, and as-builts. Forward-deploy alongside field engineers on live construction sites to turn their domain expertise into structured, queryable data models and autonomous planning tools. Requires production experience with Go/Python/TypeScript, LLM APIs, and agentic coding tools.

150k – 275k/yr
On-siteFullstack Engineering

About the role

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

  • Shipped production code in Go, Python, or TypeScript, and pick up whatever language the problem requires.
  • Built with LLM APIs (OpenAI, Anthropic, or open-weight models), created and consumed MCP servers, and shipped with agentic frameworks.
  • Work with AI coding tools like Claude Code and Cursor every day and get agents producing real work autonomously alongside you.
  • Spotted a problem no one assigned you, designed the fix, and shipped it to production with minimal direction.
  • Moved fast without leaving wreckage: systems you built under deadline are ones other engineers extended rather than rewrote.
  • Earned credibility with people who don't live in software, field engineers or cabling crews, and driven adoption of your tool on their turf.
  • 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.

Outstanding candidates may be eligible for adjusted terms, plus meaningful equity that ensures you benefit directly from the company's long-term performance.

Benefits:

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

Skills

GoPythonTypeScriptLLM APIsMcp ServersAgentic FrameworksClaude CodeCursorOtdrDcim
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