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.

Responsibilities

• Definir lo que significa "bueno" para la plataforma, establecer SLOs de latencia y tiempo de actividad para cada equipo de producto.
• Tomar decisiones importantes sobre la infraestructura, liderar las revisiones de diseño y las decisiones sobre dónde y cómo ejecutamos.
• Construir herramientas de plataforma, escribir herramientas y servicios internos que ayuden a los ingenieros a enviar, implementar y depurar más rápido.
• 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
• 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
• Hands-on AWS and GCP, including multi-cloud setups or migrations between providers

Requirements

• 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
• 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 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
• 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

Benefits

• You are self-directed and comfortable working with a globally distributed team across time zones