Software Engineer, Cloud Infrastructure
Fluidstack · San Francisco, CA
About this role
## About Fluidstack We exist to make humanity more free. Powerful AI will be the biggest lever for human choice—but only if models are aligned with what humanity actually wants. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it. Fluidstack is 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. ## How We Operate - **Be a barrel:** Full autonomy. Own things end to end; take on scope without being asked. - **Insane urgency:** Drive everything forward as fast as possible. - **Reason from first principles:** Challenge assumptions; no egos—the best idea wins. - **Love of the game:** Long hours at high intensity to push the frontier forward. - **Build something that actually matters:** Spend your time on work that matters to the world. ## Production Engineering Team — Key Problems - **Make tens of thousands of GPUs legible in real time:** Build an observability platform turning raw telemetry into signal (site health down to device/link). - **Build the control plane:** Replace one-off tooling with a stable, versioned API surface for unified machine management, state inspection, and distributed command execution. - **Keep the system’s view aligned with reality:** Integrate fleet state as a machine-readable source of truth across provisioning, operations, and customer-facing platforms. ## Role Scope - **Own the observability platform:** Build and operate data pipelines, decoration/correlation engine, and healthcheck framework to make the fleet legible—from site to device and link. - **Define and build the infrastructure API surface:** Design contracts between production infrastructure and every tool that touches it. - **Build the production control plane:** Unified machine management, state inspection, distributed command execution, and the Kubernetes-based infrastructure underpinning it. - **Own fleet state as source of truth:** SLOs, site lifecycle state, and integration with internal infrastructure management and customer-facing operations platforms. - **Land new hardware cleanly:** ZTP, DHCP, DNS, artifacts—every new XPU generation and site integration goes through IaaS before production. ## What We’re Looking For - Treat **toil as a bug** (build tools so humans don’t have to do the same thing twice). - Design **APIs that age well**; avoid leaky abstractions at scale. - Move toward **ambiguity** (build the map and explain it to others). - Learn fast in unfamiliar domains; value real competence over existing expertise. - Can **carry a pager**: run incidents, write postmortems, fix systemic causes, and move on. - Fluent with **AI tooling** (LLM APIs, MCP servers, agentic frameworks; use Claude Code/Cursor or similar daily). - Shipped **production services** other teams depend on at scale; comfortable using AI coding tools in any language. **Bonus** - Distributed systems and data pipeline engineering. - Time-series observability stacks (Prometheus, Thanos, VictoriaMetrics). - API design/versioning at scale. - Workflow/orchestration engines (Temporal, Cadence). - Hardware telemetry (BMC/Redfish). - Go, Python, Postgres. ## Salary & Benefits - Competitive total compensation (**salary + equity**) - Retirement/pension plan (local norms) - Health, de
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