Member Of Technical Staff
US$200,000 – US$290,000 / yr base salary
Posted 17 Aug 2026
Advertised as “Member of Technical Staff, AI Infrastructure Reliability”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | US$200,000 – US$290,000 / yr |
|---|
Field of studyComputer Engineering, Computer Science (or related)
Study levelBachelor's or higher
About Us:
Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
About the Role
Fireworks AI is one of the industry leaders in inference and training for open models. Open models are how the rest of the world gets to build on frontier AI without handing the keys to a single vendor, and our job is to make them fast, cheap, and dependable enough that this is a real choice. That work is systems work: GPU scheduling, kernel and runtime performance, networking, storage, Linux. We serve over 40 trillion tokens a day doing it.
Reliability Engineering makes sure that platform runs dependably as it grows. You will work across cloud infrastructure, AI systems, and product teams to make sure the pieces fit together, fail gracefully, and hold up under load.
How We Think About Ownership
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You own the bar. You define what "reliable" means at Fireworks: SLOs, error budgets, production readiness, on-call expectations. Then you drive adoption across engineering.
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You own the process and the tooling. Incident management, postmortems, observability standards, failure testing, guardrails, and automation are yours end to end.
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Every team owns the reliability of what they build. You make that ownership practical. Structured logging and aggregation, metrics and tracing that work the same way everywhere, alerting that routes to the right owner, dashboards that answer "why is this slow."
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You choose where the leverage is. You have a wide view of the platform and the latitude to spend your time where it changes outcomes most.
Responsibilities
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Define reliability standards: SLOs, error budgets, production readiness criteria. Not written in a vacuum: you instrument the systems and read the real telemetry the numbers come from.
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Own the reliability toolchain: Logging and telemetry pipelines, alerting standards, failure injection, load testing, self-healing automation, and AI-assisted investigation tooling.