Fluidstack
Technology
ProductionEngineer,Network
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Production Engineer, Network at Fluidstack. Skills: Network automation, Production engineering, AI tooling, Datacenter networking. Own network fleet health. Define realtime monitoring requirements”
What You'll Achieve.
Turn network fault into solvable problem; Define healthy network before traffic; Build civilization-scale infrastructure
Industry & Context.
Active debugging tooling; Network fault diagnosis; Root cause analysis; Troubleshooting; Systems thinking
Carry a pager
What They're Looking For.
Must Have
Own network fleet health end to end, Define realtime monitoring requirements, Build alerting lifecycle, Ship dashboards for network state, Build active debugging tooling, Link diagnostics, Remote command execution, Repair visualization, Build automation for network failure, Parts management, Return to service, Ticket integration, Repair lifecycle pipelines, Transceiver and optics tracking, Own network qualification and validation, Build frameworks for new sites, Build frameworks for hardware, Define healthy network, Own end-to-end reliability, Own scalability, Own operation of network at-scale, Aggressive automation, Aggressive tooling, Aggressive incident discipline, Treat toil as a bug, Build tools for diagnosis, Think in systems, Build tooling to differentiate faults, Move toward ambiguity, Build the map, Explain the map, Learn at steep slope, Reach competence in unfamiliar domain, Carry a pager, Run the incident, Write the postmortem, Fix systemic cause, Fluent with AI tooling, Drive Claude Code, Drive Cursor, Shipped production network tooling, Shipped production network automation
Nice to Have
Network automation and tooling, Link diagnostics, Optical network monitoring, RMA and repair lifecycle automation, Large-scale datacenter fabric, Out-of-band network management, Go, Python
What You'll Do.
Own network fleet health
Define realtime monitoring requirements
Build alerting lifecycle
Build active debugging tooling
Link diagnostics across paths
Execute commands remotely
Build repair pipeline automation
Automate fault detection
Track transceiver lifecycle
Return network to service
Define network qualification frameworks
Build network validation frameworks
Own network reliability
Own network scalability
Own network operation
Implement aggressive automation
Implement aggressive tooling
Implement aggressive incident discipline
Build diagnostic tools
Build tooling to differentiate faults
Move toward ambiguity
Learn unfamiliar domains
Drive AI coding tools
How You'll Work.
Team & Collaboration
Cross-functional teams; On-call engineers
Communication Scope
Explain maps
Full Job Description
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 - High 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. THE PRODUCTION ENGINEERING TEAM Examples of key exciting problems the team is working on - We're building the active debugging tooling that turns a network fault from a mystery into a solvable problem — link diagnostics across router-router and NIC-to-router paths, remote command execution across the fleet, and repair visualization that shows you exactly what's broken and why. - We're building the end-to-end network repair pipeline — from automated fault detection through RMA initiation, ticket integration, transceiver lifecycle tracking, and return to service
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