Staff Kubernetes Platform Engineer, Infrastructure

Location: Remote (US). Must be based in Dallas, San Francisco or New York City. Remote for now, with hybrid planned further down the road.

Pay:

• L6 (Staff): $270,400–$365,000
• L7 (Sr. Staff): $341,400–$401,600

Compensation is not an issue for the right person. The role pays nearly all cash: the bonus is folded into base, and there is an equity component on top.

A late-stage AI cloud company backed by NVIDIA, with a valuation in the billions, runs AI compute out of data centers around the world. It is now building a managed Kubernetes platform that turns large fleets of bare-metal compute into dedicated, isolated clusters for customers running AI training and inference. You'd be early on that platform in a hands-on Staff / Sr. Staff role, writing and shipping the core code and helping set its technical direction.

What you'll do

• Design and build core platform systems: APIs, controllers, operators and reconciliation loops
• Write, review, test, debug and operate production code
• Build a commercial Kubernetes service for dedicated customers running AI workloads
• Design for failure handling, consistency and recovery across distributed systems
• Define stable platform APIs that shield customers from backend changes
• Work closely with the infrastructure, inference, networking and security teams

What you bring

• A track record of shipping and maintaining production software
• Deep Kubernetes platform experience: operators, CRDs, admission control, node lifecycle
• Practical distributed systems knowledge: consensus, leader election, eventual consistency, fault domains
• A rigorous SDLC: design reviews, CI/CD, staged rollouts, rollback and observability

Nice to have: delivered a Kubernetes or infrastructure control plane as a product; hyperscaler or neocloud experience running AI or GPU workloads; inference platforms, accelerators or device plugins; daily use of coding agents like Claude Code or Codex