Staff Software Engineer (Infrastructure)

Join Stream as a Staff Software Engineer in our Infrastructure team. You'll play a crucial role in shaping our platform and infrastructure, making key decisions that impact our growth and profitability. This is a fast-paced, dynamic environment where you'll have the autonomy to set direction and make a real impact.

- A software engineer who has built systems, not only configured them. You write production code in Go, Python or a similar language. Scripting-only backgrounds are not a fit
- You write clearly. Much of this role is docs and standards that other teams will follow
- Strong system design. You can reason about failure modes, capacity and cost in distributed systems, and explain why you chose what you chose
- You treat cost and reliability as engineering problems, and you can put a number on an outcome you drove
- Solid fundamentals in networking, storage and concurrency, and the habit of asking why a system behaves the way it does instead of accepting the default
- You experiment. When you hit Kubernetes, a database or a cloud service you have not run before, you dig in, use AI to close the gap, and ship
- You are comfortable in a small team, setting direction and reviewing a PR in the same week
- You have owned high-scale production systems and set technical direction beyond your own work, through design reviews, RFCs and decisions other engineers build on
- You already use AI tools every day in your engineering work
- You would rather try something, measure it and change course than wait for a perfect plan
- You ship fast and learn fast, including when it is hectic
- You want platform and infrastructure problems at a scale most engineers never touch, and the autonomy to set the direction yourself
- You are self-directed and comfortable working with a globally distributed team across time zones
- Cloud commitment and reservation strategy (committed use discounts, savings plans), or formal FinOps practice
- Kubernetes in production: cluster architecture, workload design or a migration you led
- Open source contributions, or writing and talks on cloud, platform or distributed systems
- PostgreSQL at scale, ideally self-hosted or with CloudNativePG: sharding, replication, partitioning tradeoffs
- Real-time systems: WebSockets, WebRTC, streaming or other persistent-connection workloads
- SLO design, alert hygiene and a Prometheus and Grafana based observability stack
- Valkey or Redis at scale, ideally on Kubernetes
- Hands-on AWS and GCP, including multi-cloud setups or migrations between providers