Staff Platform Engineer, Cloud Platform

General Motors; Mountain View (CA); Hybrid; USD 160,000 - 333,000; Full time

Benefits offered by this job

Health, dental, vision insurance

Retirement savings plan

GM vehicle discounts

Job summary

General Motors seeks engineers to design and run a production-grade developer platform on GM's cloud. You will focus on a self-service experience, declarative provisioning and scalable, reliable production with AI-assisted tooling. Join a team driving fast, safe delivery and robust multi-region architecture.

You will mentor peers, set direction for platform areas, and collaborate with application teams to remove friction and accelerate shipping of software across GM.

Qualifications

• Ten or more years building and operating production infrastructure or platforms.
• Hands-on Kubernetes in production at scale with multi-tenancy, autoscaling and upgrades.
• Strong Go production coding skills.
• Experience designing internal developer platforms or cloud control planes.
• Infrastructure as code using Terraform, Crossplane, or Kubernetes operators.
• Cloud networking, identity and security, preferably Azure.
• Proven record of improving reliability with SLOs and observability.
• Strong product sense for developer experience, CLI output, docs.
• Ability to simplify and delete unnecessary systems.
• Clear written communication with stakeholders.

Responsibilities

• Design and build core platform capabilities end to end, from API design through production operations.
• Set technical direction for one or more platform areas and write the design documents.
• Eliminate toil and platform instability with code and automation.
• Create golden paths so the GM platform is the easiest way to ship.
• Use AI tooling and expose platform features to agents via APIs and MCP.
• Partner with SRE on reliability, on-call and incident reviews; define measurable SLOs.
• Mentor senior engineers, review designs and code across teams.
• Collaborate with application teams to remove platform friction.

Skills

Kubernetes

Go

Platform

IaC

Terraform

Crossplane

Azure

SRE

Observability

CLI

Incidents

Tools

Istio

ArgoCD

Kafka

MCP

AI agents

FinOps

Open source

Job description

Job Description

About the role

We want the experience of building and running software on GM's cloud to be as good as or better than what our engineers get from the best developer platforms on their own projects. Pushing code should be quick, getting a namespace or a database should take minutes, and production should stay up without heroics. We are not there yet, and that gap is the job.

What You'll Work On

• A platform people choose. Build the default way to ship software at GM so that it is easier than going around it. Move existing workloads onto it without downtime, and keep improving it based on what slows teams down.
• Self-service infrastructure. Replace hand-built and ticket-driven provisioning with declarative, API-driven infrastructure, covering networking, identity and accounts.
• Interfaces for people and agents. Design the APIs, CLI and MCP tools that engineers and AI agents use to get work done. Keep them simple and consistent, so no one needs another person in the loop to ship.
• Reliability at scale. Design for availability and scale, including cell-based and multi-region architecture. Partner with SRE to define SLOs that mean something and remove the failures that page people at night.
• Fast, safe delivery. Make the path from merge to production quick and boring, with promotion, rollback and policy built in.

What You'll Do

• Design and build core platform capabilities end to end, from API design through production operations.
• Set technical direction for one or more platform areas and write the design documents that the rest of the team builds from.
• Find the biggest sources of developer toil and platform instability, and eliminate them with code and automation rather than process or headcount.
• Build golden paths so that the right way to ship at GM is also the easiest way.
• Use AI tooling (Cursor, Claude Code and agents) as a normal part of how you build, and help make the platform itself usable by agents through APIs and MCP.
• Partner with SRE on reliability, on-call and incident reviews, and hold the platform to measurable SLOs.
• Mentor senior engineers, review designs and code across teams, and model the engineering standards we want.
• Work directly with application teams to understand where the platform gets in their way, then fix it.

What We're Looking For

• Ten or more years building and operating production infrastructure or platforms, including several years in a senior or staff role with technical leadership across teams.
• Deep, hands‑on experience with Kubernetes in production at scale, including cluster operations, multi‑tenancy, autoscaling and upgrades.
• Strong software engineering skills in Go or a comparable language. You write production code, not only configuration.
• Experience designing and running an internal developer platform, PaaS or cloud control plane that other engineers depend on.
• Expertise with infrastructure as code and declarative provisioning (Terraform, Crossplane, or Kubernetes operators and controllers).
• Solid grounding in cloud networking, identity and security, preferably on Azure.
• A track record of improving reliability with SLOs, observability and blameless incident practice.
• Strong product sense for developer experience. You care about the CLI output, the error message and the docs as much as the architecture.
• The judgment to simplify. You would rather delete a system than add another one.
• Clear written communication and the ability to bring a skeptical room along with a good design.

Nice to have

• Experience with Istio or another service mesh, Gateway API, ArgoCD, Kargo, KEDA, Karpenter or Kyverno.
• Built or migrated a large platform with zero downtime for tenants.
• Experience with event streaming platforms such as Azure Event Hubs or Kafka.
• Experience with cell‑based or multi‑region architectures.
• Built MCP servers or other interfaces designed for AI agents.
• Experience with cloud cost optimization and FinOps data pipelines.
• Contributions to open source projects in the cloud native ecosystem.

Compensation:

The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The salary range for this role is $160,200–$333,400.

The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as the geography of the selected candidate.

Bonus Potential:

An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits:

GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation and holidays, tuition assistance programs, employee assistance program, GM vehicle discounts, and more.

GM does not provide immigration‑related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1‑B, OPT, STEM OPT, CPT, TN, J‑1, etc). This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change