Principal Engineer - PVTP Architecture at General Motors in Seattle, WA

  • Company: General Motors
  • Location: Seattle, Washington, United States of America
  • Job type: full time
  • Workplace: hybrid
  • Posted: 2026-10-30

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Job description

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Seattle, WA or Warren, MI three times per week. The Role: The Physical and Virtual Test Platforms group is building the platform foundation GM engineering teams use to prepare, execute, and analyze physical and virtual tests across vehicle programs. The ecosystem spans physical test benches and assets, hardware-in-the-loop and software-in-the-loop environments, automation, simulation, virtualization, execution services, and operations. As Principal Engineer, PVTP Architecture, you will be the senior technical authority and system architect for this ecosystem. You will set the long-term architecture and drive cross-organizational solutions that improve reuse, reliability, scalability, asset readiness, execution throughput, and customer adoption. In this senior individual-contributor role you will establish interfaces and decision rights across engineering, asset operations, test execution, automation, virtual test, infrastructure, data, quality, and reliability while remaining close to implementation through architecture reviews, investigations, prototypes, and critical issue resolution. What You’ll Do Define and drive the target architecture and long-term roadmap for PVTP, spanning physical test, virtual test, automation, simulation, test assets, execution services, and platform operations. Establish the interfaces, APIs, ownership boundaries, and decision rights that enable physical and virtual environments to use common interfaces, portable workloads, reusable test capabilities, and consistent operating patterns. Shape AI strategy and investment priorities, identifying where AI-assisted workflows, agents, and analytics can improve test execution, asset readiness, operational effectiveness, and engineering productivity. Lead complex investigations and root-cause analyses across software, infrastructure, network, physical-test, virtual-test, and operational boundaries. Provide technical mentorship and direction to Staff and Principal Engineers and emerging technical leaders while establishing strong design-review and engineering-practice standards. Partner inside and outside PVTP to align solutions with broader GM needs, communicate technical risks and tradeoffs, and drive decisions with engineering, program, operations, supplier, and executive audiences. Your Skills & Abilities (Required Qualifications) Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, Systems Engineering, or a related field; or equivalent experience. Fifteen or more years of experience in software, systems, platform, infrastructure, test automation, simulation, or related engineering disciplines, including production-grade systems. Proven experience architecting complex, interdependent platforms or ecosystems that span multiple engineering teams, technology domains, and operational environments. Experience leading multi-team or cross-functional technical programs from concept through production operation and continuous improvement. Proficiency with modern engineering practices, including source control, continuous integration and delivery, automated testing, technical documentation, observability, and performance analysis. Strong communication and influence skills across technical, cross-functional, supplier, and executive audiences. What Will Give You a Competitive Edge (Preferred Qualifications) Master’s degree or equivalent experience in Computer Science, Computer Engineering, Software Engineering, Systems Engineering, or a related field. Background in automotive software, software-defined vehicles, hardware-in-the-loop, software-in-the-loop, simulation, virtualization, vehicle integration, or physical test infrastructure, with a track record integrating physical and virtual environments. Demonstrated ability to evaluate and apply approved Generative AI, AI agents, and LLM-based tools to production engin

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