Staff Kubernetes Platform Engineer, Infrastructure

Mural Group; United States; Remote; USD 270,000 - 365,000; Full time

Job summary

Mural Group is building a managed Kubernetes platform for AI workloads, with a hands-on Staff/Sr. Staff role writing and shipping core code and setting technical direction.

You’ll design and implement core platform systems, work with multiple teams, and help scale a cloud service for customers requiring isolated GPU-enabled compute.

Qualifications

• 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.

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

Distributed systems

CI/CD

APIs

SDLC processes

Code review

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