Cloud Platform Lead: Kubernetes at Scale for Autonomy

General Motors; Austin (TX); On-site; USD 233,000 - 300,000; Full time

Benefits offered by this job

Health and wellbeing benefits

Retirement savings plan

Paid vacation & holidays

Tuition assistance programs

GM vehicle discounts

Job summary

General Motors seeks a Cloud Engineering leader for Vehicle Autonomy to deliver a developer-ready PaaS, abstracting infrastructure for rapid autonomous software development. You will guide the elastic compute platform, including DNS and traffic routing, and lead a team that makes cloud-native compute a product.

The role requires expert Kubernetes (GKE preferred), large-scale platform experience, and strong leadership at the manager/principal level, with responsibility for 12,000+ namespaces

Qualifications

• Expert-level Kubernetes experience at scale.
• Experience building a Platform as a Product for large engineering teams.
• Deep understanding of cloud-native storage, Istio, and traffic engineering.
• Proven leadership at manager or principal level.

Responsibilities

• Lead the Platform Engineering/Cloud team to evolve the ACI PaaS layer for secure compute and storage.
• Own operation and scaling of 12,000+ Kubernetes namespaces across 150+ clusters (GKE-based and on-prem).
• Build/maintain rapid deployment pipelines and abstracted storage to accelerate autonomous software delivery.
• Direct DNS and traffic engineering to optimize workloads for distributed development.
• Own full capacity lifecycle for cloud resources including planning and utilization tracking.

Skills

Kubernetes (GKE) at scale

Platform as a Product

Cloud-native storage & Istio

Leadership (Manager/Principal)

Job description

General Motors seeks a Cloud Engineering leader for Vehicle Autonomy to deliver a developer-ready PaaS, abstracting infrastructure for rapid autonomous software development. You will guide the elastic compute platform, including DNS and traffic routing, and lead a team that makes cloud-native compute a product.

The role requires expert Kubernetes (GKE preferred), large-scale platform experience, and strong leadership at the manager/principal level, with responsibility for 12,000+ namespaces