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General Motors
General Motors
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General Motors is a global automotive and manufacturing company working across vehicle engineering, production, transportation, and information technology. Founded in 1908, GM develops technologies aimed at advancing mobility while pursuing its vision of zero crashes, zero emissions, and zero congestion. Its international operations bring together large, multidisciplinary teams focused on innovation, sustainable transportation, and the future of the automotive industry.
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Staff DevOps Software Engineer – VCU/CCU Infotainment Systems (Hybrid)

Lead DevOps, CI/CD, and platform engineering for General Motors’ next-generation VCU/CCU infotainment systems. Hybrid role based in Austin or Mountain View.

USUnited StatesCACaliforniaTXTexas
$189,300 – $290,700 / year
HybridFull-timeLeadEnglish RequiredDevOps Engineer
AndroidCloudDockerGrafanaGroovyJenkinsKubernetesLinuxPrometheusPythonPyTorchScikit-LearnTensorflow

Description

  • Set the technical direction and architecture for DevOps, CI/CD, and build platforms serving VCU/CCU infotainment systems
  • Create and optimize scalable CI/CD pipelines for embedded Linux Yocto builds, covering orchestration, automated testing, artifact management, and releases
  • Increase build speed and reliability with distributed build systems, caching, and infrastructure improvements
  • Automate release management through branching, versioning, artifact promotion, quality gates, and compliance validation
  • Develop self-service platforms, engineering tools, and dashboards that reduce manual work and speed delivery
  • Enhance developer productivity with GitHub automation, pull-request checks, smoke tests, and faster feedback cycles
  • Implement end-to-end observability with metrics, logs, dashboards, alerts, incident response, and root cause analysis
  • Apply AI and machine learning to predict build failures, select tests intelligently, optimize resources, detect anomalies, and prevent incidents
  • Lead cross-functional programs from initial concept through production, including architecture reviews, technical decisions, and trade-off communication
  • Coach DVE engineers on CI/CD practices, build engineering, and infrastructure design patterns
  • Advance engineering practices through code reviews, design mentorship, process improvements, hiring, and team development
  • Work with engineering, release, quality, infrastructure, and program teams to modernize software delivery

Requirements

  • Bachelor’s degree in computer science, software engineering, electrical engineering, or a related field, or equivalent practical experience
  • At least 10 years of experience in software engineering, DevOps, build engineering, platform engineering, or release engineering at staff-level scope
  • Track record of leading major technical initiatives across multiple teams from design through production deployment
  • Experience architecting and operating scalable CI/CD systems and developer platforms
  • Working knowledge of Jenkins, GitHub Actions, GitLab CI, or comparable automation tools
  • Experience with embedded Linux build systems, cross-compilation, or complex platform build pipelines
  • Programming and scripting proficiency in Python, Bash, Groovy, or a similar language
  • Experience using Docker, Kubernetes, and at least one major cloud platform
  • Hands-on experience with observability tools for metrics, logs, traces, dashboards, and alerts
  • Strong architectural judgment across APIs, workflows, integrations, automation, and reliability
  • Ability to mentor engineers, shape architecture, and deliver results in a matrixed organization
  • Preferred: background in automotive, embedded systems, infotainment, Android Automotive, Linux IVI, QNX, or related fields
  • Preferred: experience with Yocto/OpenEmbedded and ARM-based embedded platforms
  • Preferred: experience with distributed builds, remote execution, or large-scale build caching
  • Preferred: familiarity with artifact repositories, static analysis, code quality, and security scanning
  • Preferred: experience developing internal developer platforms, self-service tools, or engineering productivity solutions
  • Preferred: understanding of compliance, software quality, and release practices in regulated or safety-conscious environments
  • Preferred: experience with Datadog, Prometheus, Grafana, SonarQube, Artifactory, or comparable tools
  • Preferred: experience applying machine learning to DevOps processes
  • Preferred: familiarity with AI-assisted development, LLM code analysis, or automated root cause analysis
  • Preferred: knowledge of MLOps and deploying machine learning models within production CI/CD environments
  • Preferred: experience with TensorFlow, PyTorch, or scikit-learn

Benefits

  • Eligibility for incentive compensation based on company performance, role level, and individual results
  • Access to the company vehicle evaluation program, subject to a satisfactory motor vehicle report review
  • Relocation assistance for candidates who meet company policy requirements
  • Hybrid working arrangement
  • Benefits and Total Rewards resources
  • Reasonable workplace accommodations

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