Distributed Systems Engineer

About the role

The Production Engineering Team at Fluidstack is responsible for delivering critical infrastructure to support the deployment and operation of tens of thousands of GPUs at scale. This includes building observability platforms, designing and operating data pipelines, and ensuring that the system’s view of itself matches reality.

Responsibilities

• Own the observability platform, building and operating data pipelines, decoration and correlation engine, and healthcheck framework that make the fleet legible from site down to device and link.
• Define and build the API surface for infrastructure, designing the contracts between production infrastructure and every tool that touches it.
• Design and implement the production control plane, including unified machine management, actual state inspection, distributed command execution, and Kubernetes-based infrastructure.
• Ensure fleet state as source of truth, setting Service Level Objectives (SLOs), managing site lifecycle state, and integrating with internal infrastructure management and customer-facing operations platforms.

Requirements

Exceptional individuals who treat toil as a bug, design APIs that age well, move toward ambiguity, and learn at a steep slope are encouraged to apply. Candidates should have a strong background in distributed systems, data pipeline engineering, and time-series observability stacks such as Prometheus, Thanos, and VictoriaMetrics. Experience with API design and versioning at scale, workflow and orchestration engines like Temporal or Cadence, and BMC/Redfish or hardware telemetry is preferred. Fluency with AI tooling, particularly in areas like LLM APIs, MCP servers, and agentic frameworks, is essential. Previous experience shipping production services that other teams depend on at scale is highly valued.

Qualifications

• Experience with Go, Python, and Postgres.
• Strong understanding of Kubernetes and related technologies.
• Knowledge of distributed systems and data pipeline engineering.
• Experience with time-series observability stacks (Prometheus, Thanos, VictoriaMetrics).
• API design and versioning at scale.
• Workflow and orchestration engines (Temporal, Cadence).
• BMC/Redfish or hardware telemetry.

Skills

• Experience with AI tooling, including LLM APIs, MCP servers, and agentic frameworks.
• Ability to work independently and handle ambiguous situations.
• Strong problem-solving and debugging skills.
• Excellent communication and collaboration skills.

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.

Pay

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.

Schedule

Fluidstack offers a flexible schedule to accommodate the needs of its employees.

Contact

To apply, please submit your resume/CV along with the role you've applied for and the date you submitted your application. For any inquiries, please email careers@fluidstack.io.