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 treat toil as a bug. Manual steps in a repair workflow are a backlog item, not a job description.
You have an instinct for hardware. You're comfortable reasoning about failure modes at the firmware and silicon level, not just the software stack above it.
You move toward ambiguity, not away from it. You walk into the fog, build the map, and explain it to everyone else.
You learn at a steep slope. You reach real competence in an unfamiliar domain fast. We value this over existing expertise.
You carry a pager without flinching. You run the incident, write the postmortem, fix the systemic cause, and move on.
You're fluent with AI tooling. LLM APIs, MCP servers, and agentic frameworks, and you drive Claude Code, Cursor, or similar every day.
You've shipped production automation that other teams depend on, and you're comfortable in any language using AI coding tools.
Bonus: Hardware lifecycle management and RMA automation. BMC/Redfish or IPMI tooling. GPU/TPU qualification or burn-in frameworks. Workflow and orchestration engines (Temporal, Cadence). Metrics and alerting pipelines (Prometheus, Grafana). Go or Python.
Salary & Benefits
Competitive total compensation package (salary + equity).
Retirement or pension plan, in line with local norms.
Health, dental, and vision insurance.
Generous PTO policy, in line with local norms.
The base salary range
Benefits
Health insuranceDental insuranceVision insurancePaid time offEquity / stock optionsPerformance bonus
Additional Information
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 automation that takes a XPU failure from detection through triage, hospital queue, RMA, and return to service - replacing manual procedures with a repair pipeline that runs itself.
We're standing up the XPU qualification platform that defines what "production-ready" means for every new XPU generation - burn-in, performance baselining, and NPI execution, before a single chip carries customer workload.
We're migrating clusters across multiple live sites to a new operational model simultaneously - converting clusters, bringing new sites online, and making Kubernetes-orchestrated bare metal compute operationally sustainable at scale.
We're bringing deep visibility and operational excellence to the compute space. Our team has the ability to orchestrate, debug, and performance test compute infrastructure at hyperscale.
Role Scope
Own compute fleet health end to end. Build the metrics pipelines, alerting, and unified health view that tell you the true state of every GPU and TPU in production - across Kubernetes-orchestrated workloads and bare metal, at scale.
Turn repair into a pipeline, not a procedure. Build and own the automation that takes a compute failure from detection through triage, parts management, and return to service. No one-off scripts, no heroics.
Design and expand the XPU qualification platform. Burn-in, performance baselining, and NPI execution for every new GPU and TPU generation. You define what "good" looks like before hardware goes into production.
Own Redfish and BMC tooling. Firmware-level telemetry, log collection at fleet scale, and the low-level access layer that repair automation and health tooling depend on.
Own end-to-end reliability, scalability, and operation of the compute fleet at-scale. Fluidstack is building one of the largest XPU fleets in the world and that can only be accomplished with aggressive automation, tooling, and incident discipline.
Fluidstack · San Francisco, CA