Staff Kubernetes Platform Engineer, Infrastructure

Mural Group; San Francisco (CA); Remote; USD 270,000 - 402,000; Full time

Job summary

Mural Group is building a managed Kubernetes platform for AI workloads. You’ll join as Staff or Sr. Staff to design, implement, and ship core platform software that scales across data centers and customers.

You’ll contribute to APIs, operators, and services, collaborating with infra, inference, networking and security teams to deliver robust, fault-tolerant systems at scale.

Qualifications

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

Responsibilities

• 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

Skills

Kubernetes platform experience

Distributed systems

SDLC / CI/CD

Production software

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