Principal Software Engineer - Embedded Software Platform

General Motors
Milford Charter Township, MI, United States
20 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis AUTomotive Open System Architecture (AUTOSAR) Cloud Computing Cloud Engineering Continuous Integration Linux on Embedded Systems Embedded Software Cloud Services Software Engineering Systems Architecture
+17 more
Systems Integration Test Data Test Execution Engine Toolchain Virtualization Technology Macros Delivery Pipeline Hardware Testing Caching Yocto Git Flow Kubernetes Infrastructure Automation Frameworks Github Enterprise Build Tools Terraform Service Stack

Job description

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)., General Motors is seeking a Principal Software Engineer to set technical direction for the engineering platforms that build, test, integrate, validate, and deliver embedded software for software-defined vehicles. This role is for an enterprise-level technical authority who can define the future-state engineering system, resolve architectural issues that span organizations and domains, and turn strategy into durable platforms, standards, and operating mechanisms.

The successful candidate will shape direction across multiple technical areas and organizations, advise senior and executive leadership on complex tradeoffs, and create alignment across embedded software, cloud, simulation, test, release, cybersecurity, quality, and supplier ecosystems. The role may align to one or more of the four specialization areas below.

E xpectations and I mpact :

  • Set multi-year technical direction and target-state architecture for a broad, cross-domain capability or interconnected set of platform capabilities.
  • Identify systemic constraints and opportunities across the software lifecycle, then define the strategy, investment priorities, and sequencing required to address them.
  • Resolve the most ambiguous and consequential architectural tradeoffs spanning organizations, product lines, suppliers, technology stacks, and delivery cadences.
  • Establish enterprise-level principles, standards, governance, reliability expectations, and decision frameworks that scale beyond a single program or team.
  • Create leverage through platforms, automation, reusable patterns, data, and operating models that materially improve engineering effectiveness and product outcomes.
  • Influence senior and executive leaders through clear recommendations grounded in technical judgment, risk, cost, quality, and measurable business impact.
  • Lead through other technical leaders by developing principal and staff engineers, strengthening communities of practice, and raising the quality of architectural decisions.
  • Remain technically credible and selectively hands-on in the highest-value or highest-risk problems.

Specialization A reas :

  1. Virtualization and CI infrastructure

Set the strategy for a scalable virtual development platform spanning embedded, simulation, and cloud workloads. Define enterprise architecture and standards for CI/CD, GitOps, Kubernetes, Terraform and infrastructure as code, progressive delivery, artifact and environment management, security, compliance, and observability. Connect virtualized development to the broader vehicle software lifecycle and guide adoption across organizations., * Define the future-state architecture and multi-year roadmap for the assigned domain and its interfaces with adjacent domains.

  • Establish principles, standards, governance, and decision rights that align independent teams and delivery organizations.
  • Lead the resolution of cross-domain technical risks involving architecture, quality, security, reliability, cost, scalability, and delivery continuity.
  • Advise senior and executive leadership on investment choices, program risk, platform health, and tradeoffs between local optimization and enterprise value.
  • Convene architecture reviews and technical communities that create durable alignment across engineering, validation, cloud, cybersecurity, qua

Requirements

  • Significant experience setting architecture and technical direction for CI/CD platforms spanning embedded, simulation, and cloud workloads.
  • Deep experience with Kubernetes cluster operations, Terraform or comparable infrastructure-as-code module design, and production cloud architecture.
  • Experience establishing enterprise standards for security, compliance, progressive delivery, artifact flows, and observability.
  • Demonstrated ability to drive adoption of a common virtual development platform across organizations or product lines.
  1. Continuous integration and quality gating

Set the end-to-end architecture and policy for how vehicle software is built, composed, validated, promoted, and released. Define the quality-gating model, mainline-protection strategy, evidence standards, integration controls, and release-readiness framework across component, pillar, system, virtual, physical, and release-train flows. Establish the metrics and operating mechanisms that make quality signals trustworthy and delivery risk visible.

CI and Quality-related basic qualifications

  • Significant experience defining enterprise CI/CD architecture, quality-gating policy, and release-readiness frameworks for embedded or vehicle software.
  • Deep understanding of MCU and SoC build systems, embedded Linux, AUTOSAR, Yocto, containers, cross-compilation, or vehicle deployment workflows.
  • Experience governing GitHub Enterprise or comparable platforms, artifact promotion, virtual and hardware validation, and secure delivery controls.
  • Demonstrated ability to align multiple organizations around objective quality signals, integration standards, and release policy.
  1. Test-system modernization

Set the long-term architecture and modernization strategy for embedded test execution across virtual and physical environments. Establish common approaches to configuration and variation management, change-impact analysis, risk-based regression, result-data modeling, diagnostics, APIs, analytics, and failure triage. Create a connected test ecosystem that improves traceability, execution efficiency, learning from test data, and decision quality across the vehicle software lifecycle.

Test-specific basic qualifications

  • Significant experience setting architecture and modernization strategy for large-scale embedded test systems across virtual and physical environments.
  • Deep expertise in variation management, configuration comparison, change-impact analysis, and risk-based regression strategies.
  • Experience defining common test-result data models, APIs, analytics, diagnostics, and integrations across multiple engineering organizations.
  • Demonstrated ability to establish enterprise test standards that improve traceability, execution efficiency, failure triage, and decision quality.
  1. Build-system modernization

Set the enterprise strategy for scalable embedded build systems and developer productivity. Define migration and convergence patterns for legacy Make or shell workflows and Bazel-based systems; establish standards for rules, toolchains, platforms, reproducibility, caching, security, provenance, and release integration; and guide adoption across repositories, teams, and product lines. Evaluate emerging AI-assisted engineering capabilities using clear quality, adoption, and productivity measures.

Build System-specific basic qualifications

  • Significant experiencesetting enterprise build-system architecture and developer-productivity strategy for embedded software.
  • Deep experience leading large-scale migration from Make or shell-based orchestration to Bazel or a comparable build platform.
  • Experience defining reusable rules, macros, toolchains, platforms, repository standards, artifact provenance, and reproducible build practices.
  • Demonstrated ability to guide adoption and measure quality, reliability, capacity, developer feedback, and productivity outcomes across organizations.

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