Member of Technical Staff, AI Infrastructure Reliability

Job summary

Responsibilities

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.

• 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…
• Own the reliability toolchain: Logging and telemetry pipelines, alerting standards, failure injection, load testing, self-healing automation, and AI-assisted investigation tooling.
• Keep customer experience from falling through the cracks: Per-service reliability is necessary but not sufficient.
• Own the seams: The hardest failures live between systems: retries that amplify load, timeouts that do not compose, dependencies nobody mapped.
• Run incident management: Coordinate live production issues, run blameless postmortems, and track follow-ups to completion.

What they're looking for

• Systems fundamentals: 5+ years with Linux internals, system performance troubleshooting, and networking fundamentals (TCP/IP, HTTP, gRPC).
• Software engineering: 5+ years in Python, Go, C++, or Rust, writing production-grade tools and systems code.
• Cloud-native operations: Operating and debugging Kubernetes, Terraform, and Docker in high-throughput production.
• Distributed systems: High-throughput control planes, microservices, or multi-region setups.
• Reliability fundamentals: Fault-tolerant design, SLO/SLA management, automated failover, high-availability architecture.

Tech stack

• PyTorch
• Python
• Go
• C++
• Rust
• Kubernetes
• Terraform
• Docker