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General Motors

Staff Software Engineer - Embedded Software Platform

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What they do

A Platform Engineer is responsible for the development of platforms that support the needs and use cases of different engineering teams across the organization. Creates reusable tools and workflows to streamline operational needs and facilitate automation tasks, supporting scalability of DevOps practices.

$135,341 / year median in Michigan

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Job Description

Remote/Hybrid Milford, Michigan, United States of America Austin, Texas, United States of America Mountain View, California, United States of America Warren, Michigan, United States of America Full time
JR-202619549
Job Description Work Arrangement:
This role is based remotely, but if the candidate lives within a 50 miles radius of a GM hub, they will be expected to report to the location three times a week (or other frequency dictated by your manager). T he R ole : General Motors is seeking a Staff Software Engineer to shape and scale the engineering platforms that build, test, integrate, validate, and deliver embedded software for software-defined vehicles. This role is for a hands-on technical leader who can turn ambiguous, cross-team problems into durable architecture, practical standards, and measurable improvements in engineering effectiveness, release confidence, and product quality. The successful candidate will lead a major capability across multiple teams, influence technical direction beyond their immediate organization, and connect software, tooling, infrastructure, test, and release activities into a coherent engineering system. The role may align to one or more of the four specialization areas below. E xpectations and I mpact : Own the architecture, technical roadmap, and execution strategy for a significant platform capability or a set of related initiatives. Lead high-impact, multi-team technical efforts from problem definition through adoption and operationalization. Establish reusable patterns, standards, quality controls, and developer experiences that improve consistency and speed across teams. Make sound architectural decisions in complex embedded, real-time, cloud, simulation, test, and release environments. Use engineering data and operational signals to prioritize improvements in reliability, feedback time, quality, and developer productivity. Influence without relying on direct authority; align engineering, validation, cybersecurity, cloud, quality, program, and supplier stakeholders. Remain hands-on in the most difficult technical problems while enabling others through coaching, mentoring, documentation, and technical leadership. Communicate tradeoffs, risks, progress, and recommendations clearly to senior engineering and program leaders. Specialization A reas : Virtualization and CI infrastructure Define and evolve the platform used to build, test, and deploy virtualized vehicle software across embedded, simulation, and cloud environments. Work may include enterprise CI/CD architecture, GitOps delivery on Kubernetes, Terraform and infrastructure-as-code patterns, progressive delivery and rollback, artifact flows, security and compliance integration, and observability for pipelines and simulation workloads. Virtualization- specific basic qualifications Experience designing or delivering CI/CD platforms for embedded, simulation, or cloud workloads. Hands-on experience with Kubernetes, Terraform or comparable infrastructure-as-code practices, and production cloud environments. Experience with embedded or simulation workflows such as vECUs, SIL, FMU, or SSP. Ability to translate platform architecture into reusable automation, standards, and operational practices. 2. Continuous integration and quality gating Architect traceable delivery flows that safely move software and related inputs from pull request through component, system, virtual, physical, and release validation. Work may include GitHub Enterprise workflows, artifact promotion, dependency and configuration management, mainline protection, tiered quality gates, test-evidence policy, embedded and vehicle-level compatibility checks, release readiness, and pipeline-health metrics. CI-specific basic qualifications Experience architecting or implementing end-to-end CI/CD and quality-gating workflows for embedded software. Experience with GitHub Enterprise or comparable source-control and pipeline platforms, artifact repositories, and automated test evidence. Understanding embedded and vehicle-system integration across ECUs, MCUs, SoCs, containers, networks, configuration, or calibration. Experience incorporating static analysis, security scanning, coverage, integration testing, simulation, or hardware-based validation into delivery controls. 3. Test-system modernization Modernize large-scale embedded test systems so standardized, headless, automated testing can run repeatedly across virtual and physical environments. Work may include test execution architecture, configuration and variation management, change-impact analysis, risk-based regression selection, test-result schemas and APIs, Databricks-enabled analytics, diagnostics, failure triage, and integration with CI/CD, test management, and issue-management workflows. Specialization-specific basic qualifications Experience architecting embedded test automation and build-to-test pipelines across virtual or physical environments. Experience with configuration and variation management, change-impact analysis, or risk-based regression testing. Experience modeling test results and integrating test execution with APIs, analytics platforms such as Databricks, diagnostics, or issue-management workflows. Proficiency with engineering automation tools such as Linux, Git, Python, Bash, Robot Framework, containers, or infrastructure as code. 4. Build-system modernization Modernize embedded build and test infrastructure by creating scalable, reproducible, secure, and developer-friendly workflows. Work may include transitioning legacy Make or shell orchestration to Bazel, developing reusable rules, macros, toolchains, platforms, and repository standards, migrating firmware and generated code, integrating build systems with CI/CD and release processes, improving caching and parallelism, and evaluating AI-assisted engineering workflows with measurable outcomes. Build System-specific basic qualifications Experience building and maintaining production software systems, with proficiency in Python and at least one additional engineering-tooling language. Experience in automotive, embedded, safety-related, calibration, or systems-engineering environments. Experience migrating Make or shell-based build orchestration to Bazel or a comparable scalable build system. Experience with embedded cross-compilation, toolchains, generated code, firmware, build reproducibility, or CI/CD integration. What Y ou'll D o : Define target-state architecture, phased roadmaps, and implementation priorities for the assigned capability. Lead architecture reviews, technical working sessions, design decisions, and cross-functional alignment. Identify manual handoffs, duplicated work, late integration points, unreliable signals, and other systemic sources of delay or quality escape. Deliver or guide production-quality software, automation, platform components, and integrations. Create standards and reusable patterns that make the preferred engineering path the easiest path for product teams and suppliers. Establish clear ownership, entry and exit criteria, operational expectations, and exception-management practices. Instrument the platform and use data to identify root causes, guide investment, and demonstrate measurable improvement. Partner with teams responsible for embedded software, vehicle integration, validation, developer experience, cloud, cybersecurity, artifact management, and program delivery. Coach senior engineers and help grow technical leadership across the organization. Your Skills & Abilities (Required Qualifications): Bachelor's degree in computer science, computer engineering, electrical engineering, software engineering, systems engineering, or a relat