# Site Reliability Engineer, Compute

**Company:** [Fluidstack](https://hotfix.jobs/companies/fluidstack)
**Location:** San Francsisco, CA, New York, NY, Austin, TX, Seattle, WA
**Role:** DevOps / SRE
**Salary:** $175k – $300k/yr
**Experience:** 5+ years
**Skills:** Kubernetes, Redfish, Bmc, Prometheus, Grafana, Go, Python, Temporal, Cadence, Ipmi
**Posted:** 2026-07-05

> Own end-to-end health, reliability, and automation for a massive GPU compute fleet at Fluidstack. Build metrics, repair pipelines, GPU qualification platforms, and low-level BMC/Redfish tooling while driving incidents and using AI coding tools daily. Hardware intuition and comfort with ambiguity required.

## Job Description

## Responsibilities
- Own compute fleet health end to end: build metrics pipelines, alerting, and unified health view for every GPU in production across Kubernetes-orchestrated workloads and bare metal at scale.
- Turn deployment and repair into a pipeline: build and own automation that takes a compute failure from detection through triage, parts management, and return to service.
- Design and expand the GPU qualification platform for burn-in, performance baselining, and NPI execution for every new GPU generation; define what "production-ready" means.
- Own Redfish and BMC tooling, including firmware-level telemetry, log collection at fleet scale, and the low-level access layer.
- Own end-to-end reliability, scalability, and operation of the compute fleet at scale through aggressive automation, tooling, and incident discipline.
- Build the repair pipeline that keeps pace with a 10 GW fleet, automating from fault detection through triage, RMA, and return to service.
- Qualify every new GPU generation inside a 6-month build window.
- Migrate live compute at construction speed across production sites.
- See and own the entire fleet in real time at any scale: build observability and orchestration layer.
- Debug, tune, and performance-test infrastructure that grows rapidly.

## Requirements
- Treat toil as a bug: manual steps in repair workflows are backlog items.
- Instinct for hardware: comfortable reasoning about failure modes at firmware and silicon level.
- Move toward ambiguity: build the map in unclear situations.
- Learn at a steep slope: reach real competence in unfamiliar domains quickly.
- Carry a pager: run incidents, write postmortems, fix systemic causes.
- Fluent with AI tooling: use LLM APIs, MCP servers, agentic frameworks, Claude Code, Cursor, or similar daily.
- Shipped production automation that other teams depend on; comfortable in any language using AI coding tools.

## Nice-to-Haves
- Hardware lifecycle management and RMA automation.
- BMC/Redfish or IPMI tooling.
- GPU qualification or burn-in frameworks.
- Workflow and orchestration engines (Temporal, Cadence).
- Metrics and alerting pipelines (Prometheus, Grafana).
- Go or Python.

## Similar roles

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- [Production Engineer, Compute](https://hotfix.jobs/jobs/fd05f1e5-25dc-4cc1-838c-121d9ad18c39) - Fluidstack - San Francisco, CA - $175k – $300k/yr
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**Apply:** https://hotfix.jobs/jobs/4374777f-3589-4aac-bd7c-61c791f5a467
**Canonical:** https://hotfix.jobs/jobs/4374777f-3589-4aac-bd7c-61c791f5a467