The Production Engineering TeamExamples of key exciting problems the team is working on- We're building the observability platform that makes a fleet of tens of thousands of XPUs legible in real time - from site-level health down to individual device and link, with a data decoration and correlation engine that turns raw telemetry into signal.
- We're designing the API surface that every team at Fluidstack uses to interact with production infrastructure - replacing one-off tooling with a stable, versioned control plane that includes unified machine management, actual state inspection, and distributed command execution.
- We're integrating fleet state as a machine-readable source of truth across provisioning, operations, and customer-facing platforms - so that what the system says about itself always matches reality, and every new site and XPU generation lands cleanly from day zero.
Role Scope- Own the observability platform. Build and operate the data pipelines, decoration and correlation engine, and healthcheck framework that make the fleet legible - from site down to device and link. No other team should need to scrape production directly to answer a question.
- Define and build the API surface for infrastructure. Design the contracts between production infrastructure and every tool that touches it. All other teams at Fluidstack use your tooling to manage and operate our hyperscale fleet.
- Build the production control plane. Unified machine management, actual state inspection, distributed command execution - and the Kubernetes-based infrastructure that underpins it all.
- Own fleet state as source of truth. SLOs, site lifecycle state, and integration with internal infrastructure management and customer-facing operations platforms. What the system says about itself should match reality, and you're accountable when it doesn't.
- Land new hardware into the platform cleanly. ZTP, DHCP, DNS, artifacts - every new XPU generation and site integration goes through IaaS before production.
What We're Looking ForThe 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. If something requires a human to do it twice, you build the thing that makes it not require a human.
- You design APIs that age well. You've felt the pain of a leaky abstraction at scale and you don't repeat 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 services that other teams depend on at scale, and you're comfortable in any language using AI coding tools.
- Bonus: Distributed systems and data pipeline engineering. Time-series observability stacks (Prometheus, Thanos, VictoriaMetrics). API design and versioning at scale. Workflow and orchestration engines (Temporal, Cadence). BMC/Redfish or hardware telemetry. Go, Python, and Postgres.
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 for this position is $175,000 - $300,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.
We are committed to pay equity and transparency.
