General Motors
Staff Software Engineer for NextGen In-Vehicle Infotainment Systems - DevOps
$189K–$291K
Mountain View, California, United States of America +3 · Hybrid · Staff · Full-time · Posted Oct 14, 2026
- Location
- Mountain View, California, United States of America
Seattle, Washington, United States of America
Austin, Texas, United States of America
Warren, Michigan, United States of America - Experience
- 10+ years; includes leading large multi-team technical initiatives from design through production.
- Education
- Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or related field, or equivalent practical experience.
About the job
Leads architecture and delivery of build, CI/CD, release, and developer productivity platforms for next-generation infotainment software.
What you'll do
- Set technical strategy and build scalable CI/CD systems for infotainment, including embedded Linux builds, testing, artifacts, and release workflows.
- Automate releases and develop self-service platforms, GitHub automation, and dashboards to improve developer productivity.
- Lead operational excellence and cross-functional initiatives; mentor engineers and influence technical direction.
What they ask for
- Bachelor's degree in a related field or equivalent practical experience.
- 10+ years in software, DevOps, build, platform, or release engineering at staff-level scope, including leading large multi-team initiatives from design through production.
- Experience designing and operating scalable CI/CD systems and developer platforms.
- Embedded Linux or complex platform build experience, programming/scripting skills, cloud/container experience, and hands-on observability practice.
Nice to have
- Automotive, embedded, infotainment, Android Automotive, Linux IVI, QNX, Yocto/OpenEmbedded, or ARM platform experience.
- Distributed build systems, developer platforms, artifact/security/observability tooling, or AI/ML applied to DevOps.
Pay
$189,300 to $290,700 USD base salary
Tools
Jenkins, GitHub Actions, GitLab CI, Python, Bash, Groovy, Docker, Kubernetes
AI focus
Preferred experience applying AI/ML to DevOps workflows, such as predictive build failures, intelligent test selection, and anomaly detection, or familiarity with AI-assisted engineering tooling.
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