Production Engineer, Network

About the role

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

- 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 PRODUCTION ENGINEERING TEAM

Examples of key problems the team is working on

- Turn every network fault from a mystery into a closed ticket. Link diagnostics across router to router and NIC to router paths, remote command execution across the fleet, and repair visualization that shows what's broken and why, because at 10s of GW scale debugging has to be systematic, not artisanal.

- Build the network repair pipeline that runs itself. Automated fault detection through RMA initiation, ticket integration, transceiver lifecycle tracking, and return to service, across DC fabric, edge, and host to network layers, because a new site comes online every six months and manual repair doesn't keep up.

- Build the network monitoring platform for a fleet that never stops growing. Alerting lifecycle and health dashboards for infrastructure spanning multiple hyperscale sites today and 10s of GW next year. It doesn't exist yet. We're building it.

Role Scope

- Carry the on-call pager for the network fleet and run repair end to end: diagnose the fault, execute the fix or drive the RMA, and return the link to service across DC fabric, edge, and host to network layers.

- Write Python and Go tooling that replaces manual diagnosis, including link tests, remote command execution across the fleet, and repair visualization that shows what's broken and why, so faults resolve in minutes, not hours.