Staff Software Engineer for NextGen In-Vehicle Infotainment Systems - DevOps at General Motors in Mountain View, CA

  • Company: General Motors
  • Location: Mountain View, California, United States of America
  • Job type: full time
  • Workplace: hybrid
  • Posted: 2026-10-14

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Job description

Job Description Work Arrangement: This role is categorized as hybrid . This means the successful candidate is expected to report to Austin, TX, Mountain View, CA, Warren, MI or Seattle, WA three times per week, at minimum. About the Role Own the technology that powers next-generation infotainment. At General Motors, you'll build the delivery engine that moves software from engineers' hands into vehicles driven by millions of people every day. We're tackling software-defined vehicles at a scale few companies can match and we need a Staff Software Engineer ready to accelerate that mission. You'll make software delivery faster, smarter, and more reliable, shaping how GM delivers the future of driving. This role combines deep technical execution with cross-functional leadership. You will drive the architecture, implementation, and operational excellence of the build, test, release, and developer productivity ecosystem that enables reliable software delivery at scale. In line with GM's staff-level engineering expectations, this role requires end-to-end ownership, strong architectural judgment, and the ability to influence technical direction across teams without direct authority. You will partner closely with engineering, release management, quality, infrastructure, and program stakeholders to modernize CI/CD, improve developer velocity, strengthen observability, and raise the quality and reliability bar for NextGen infotainment software delivery. What You'll Do Define technical strategy and architecture for DevOps, CI/CD, and build platforms supporting NextGen infotainment across multiple vehicle programs Design and optimize scalable CI/CD pipelines for embedded Linux (Yocto) builds, including orchestration, test automation, artifact management, release workflows, distributed builds (BuildBarn/RBE), and caching Automate release processes including branching, versioning, artifact promotion, quality gates, and compliance checks Build self-service platforms, GitHub automation, and dashboards that cut manual effort and accelerate developer feedback loops Drive end-to-end observability and operational excellence, and lead cross-functional initiatives from concept to production while mentoring engineers and raising the bar through design reviews, process improvement, and hiring Your Skills & Abilities (Required Qualifications) Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or related field, or equivalent practical experience 10+ years in software engineering, DevOps, build engineering, platform engineering, or release engineering at staff-level scope, including leading large multi-team technical initiatives from design through production Strong experience designing and operating scalable CI/CD systems and developer platforms (Jenkins, GitHub Actions, GitLab CI, or similar) Experience with embedded Linux build systems, cross-compilation environments, or complex platform build pipelines, plus strong programming/scripting skills (Python, Bash, Groovy, or similar) and cloud/container experience (Docker, Kubernetes, and at least one major cloud) Hands-on observability practice (metrics, logging, tracing, dashboards, alerting) with the ability to mentor, influence architecture, and execute in a matrixed organization What Will Give You a Competitive Edge (Preferred Qualifications) Experience in automotive, embedded systems, infotainment, Android Automotive, Linux IVI, QNX, or related domains Experience with Yocto / OpenEmbedded and ARM-based embedded platforms Experience with distributed build systems, remote build execution, large-scale build caching, and building internal developer platforms or engineering productivity solutions Familiarity with artifact repositories, static analysis, code quality, and security scanning tools (e.g., Artifactory, SonarQube), plus observability/delivery tooling such as Datadog, Prometheus, or Grafana in large multi-repo / multi-team release programs Experience applying AI/

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