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Staff Kubernetes Platform Engineer, Infrastructure

πŸ•’ 6 days ago
KubernetesKubernetes OperatorsCustom Resource Definitions (crds)Admission Control
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πŸ“œ Description

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

πŸ› οΈ Requirements

  • 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

✨ Benefits

  • Bonus folded into base compensation.
  • Equity component.
Full job description

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

Mural Group is recruiting for this role on behalf of a client. Apply here and a Mural recruiter will be in touch.

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