Summary
What you’ll impact
The Senior Platform Engineer is responsible for designing, building, and operating software platforms that monitor and manage large fleets of AI compute clusters. The role uses Go, Protocol Buffers, SQL, and Python on Linux containers and Kubernetes to build control‑plane services and APIs. Key duties include developing scalable backend services, integrating data from multiple infrastructure systems, automating incident response workflows, and ensuring high‑availability through testing and observability. The engineer collaborates with cluster operations, infrastructure, security, and data‑center teams, leads project delivery from design to production, and provides guidance to peers.
Responsibilities
What you'll do
- Build and operate software for managing large fleets of AI clusters
- Give operators clear, actionable views of cluster health, capacity, performance, and ongoing issues.
- Develop services and integrations that bring together data and workflows from multiple infrastructure systems.
- Automate repetitive work and improve the tools teams use to investigate incidents and restore service.
- Design systems that remain reliable as the fleet grows and continue to function through component and site failures.
- Work closely with users of the platform to understand their needs and make practical product and engineering decisions.
- Lead projects from initial design to production, measure their impact, and use operational feedback to guide improvements.
Requirements
What you’ll bring
- 12+ years of industry experience building and operating production distributed systems or large-scale infrastructure software.
- Strong Go skills. You will work with Go, Protocol Buffers, and SQL regularly. Python experience is an added benefit.
- Experience building control planes, fleet management systems, or operational platforms.
- Experience designing APIs and data models that serve multiple consumers, with a considered approach to versioning and compatibility.
- Experience building asynchronous systems that support idempotency, concurrency, and reconciliation while preventing unintended state drift.
- A strong testing practice, especially for software that can change the state of running production clusters.
- Experience with Linux, containers, and Kubernetes.
- Experience with durable workflow execution, event streaming, or time-series telemetry at high cardinality.
- Sound judgment about reliability, security, and observability, including how a system behaves when its dependencies are unavailable.
- Ability to take an ambiguous problem from design through production and improve the solution using operational feedback.