Staff Network Engineer, Deployment

Reposted Yesterday
Be an Early Applicant
4 Locations
In-Office
253K-295K Annually
Senior level
Artificial Intelligence • Software
The Role
Lead technical execution of large-scale network deployments: define ZTP and validation playbooks, set acceptance criteria, resolve escalations across links and fabrics, and automate turn-up processes to eliminate manual repetition.
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!

How We Operate
  • Extreme 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.

Role Scope
  • Own technical execution of network deployment: the standards, tooling, and hardest problems across every site turn-up.

  • Set the technical playbook: ZTP flows, validation suites, and acceptance criteria per fabric.

  • Take the escalations nobody else can close: the link that won't train, the fabric that won't converge.

  • Automate the turn-up: anything done twice by hand becomes tooling.

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 been the senior technical hand on large network deployments.

  • You've built ZTP and validation automation that ran at scale.

  • You debug link and fabric issues from optics to routing.

  • Deployments you've led finished clean, with no punch list of mystery links.

  • Bonus: InfiniBand and RoCE. 100k+ GPU fabrics. Python or Go automation. Optics-level debugging.

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

  • Senior technical lead on large network deployments
  • Built ZTP and validation automation at scale
  • Debug link and fabric issues from optics to routing
  • Automate turn-up processes; convert repeated manual tasks into tooling
  • Deployments completed cleanly with no unresolved mystery links
  • InfiniBand and RoCE experience
  • Experience with 100k+ GPU fabrics
  • Python or Go automation experience
  • Optics-level debugging experience
Am I A Good Fit?
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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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