Staff MPU Triage and Automation Engineer

Stellantis•Auburn Hills, MI

About The Position

We are seeking a Staff MPU Triage and Automation Engineer responsible for triaging, debugging, root cause analysis, and automation of software issues on automotive High Performance Computing (HPC) platforms running Android and QNX on Qualcomm-based, hypervisor-enabled architectures. The engineer will serve as a technical leader for issue investigation across Android, QNX, Hypervisor, BSP, Middleware, Applications, Connectivity, and Vehicle Interface domains. The role involves identifying fault ownership, driving cross-functional problem resolution, improving engineering efficiency through automation, and developing AI-assisted solutions to accelerate debugging, validation, and testing activities. The engineer will collaborate with platform, BSP, middleware, validation, integration, and supplier teams to improve software quality, reduce issue resolution time, and support the delivery of reliable and production-ready vehicle software.

Requirements

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
Minimum 8 years of experience in Embedded Software Development, System Integration, Validation, or Software Debugging.
Experience working with Android and QNX embedded platforms.
Strong understanding of automotive software architecture, BSPs, middleware, device drivers, and platform software.
Experience debugging complex software issues across multiple software domains.
Strong knowledge of operating system fundamentals, processes, threads, memory management, and system-level debugging.
Proficiency in C/C++, Python, and Shell scripting.
Strong experience with Linux-based development environments.
Experience analyzing logs, crash dumps, memory leaks, watchdog resets, boot failures, and performance bottlenecks.
Experience with Git, CI/CD pipelines, and software release processes.
Knowledge of automotive communication protocols including CAN, Ethernet, SOME/IP, TCP/IP, UDP, and diagnostics.
Experience working with automotive SoCs and High Performance Computing (HPC) platforms.
Strong root cause analysis, problem-solving, and debugging skills.
Strong communication, collaboration, and technical leadership skills.

Nice To Haves

Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Experience with Qualcomm Snapdragon automotive platforms.
Experience working with hypervisors, virtualization technologies, and multi-OS architectures.
Experience debugging Android-QNX communication, shared resources, virtualization, networking, audio, graphics, storage, or vehicle interface issues.
Experience with automotive infotainment, digital cockpit, ADAS, or HPC vehicle compute platforms.
Experience with CAN, Ethernet, SOME/IP, diagnostics, flashing, HIL, and vehicle integration activities.
Experience developing automation frameworks, triage dashboards, and engineering productivity tools.
Hands-on experience with GitHub Copilot, Microsoft Copilot, Claude, or similar AI development platforms.
Familiarity with AI agents, prompt engineering, agentic AI workflows, and tool integration.
Experience integrating AI solutions with GitHub, Jira, CI/CD pipelines, dashboards, and internal engineering platforms.
Understanding of functional safety (ISO 26262) and automotive cybersecurity (ISO/SAE 21434).
Experience leading technical initiatives across global engineering organizations and supplier teams.

Responsibilities

Analyze, triage, and reproduce software issues across Android, QNX, Hypervisor, BSP, Middleware, Drivers, and Application layers.
Investigate system logs, traces, crash dumps, watchdog resets, boot failures, memory leaks, performance issues, and communication failures.
Identify the probable fault domain and route issues to the appropriate software, hardware, platform, validation, or supplier teams.
Drive root cause analysis activities and track issues through closure and verification.
Debug cross-domain interactions between Android, QNX, Hypervisor, middleware services, and shared hardware resources.
Support software integration, validation, and release activities across multiple vehicle programs.
Develop automation tools using Python, Shell scripting, and similar technologies for log collection, analysis, issue classification, testing, and reporting.
Build dashboards and automated workflows to improve triage efficiency, defect tracking, and engineering productivity.
Develop and maintain troubleshooting guides, known issue databases, and debugging procedures.
Leverage GitHub Copilot, Microsoft Copilot, Claude, and other AI-assisted development tools to improve debugging, automation, documentation, and test generation.
Develop AI agents, reusable skills, prompts, and workflows to automate engineering and triage activities.
Validate AI-generated code and technical outputs for correctness, security, maintainability, and compliance.
Contribute to CI/CD pipelines, software quality initiatives, and continuous integration activities.
Provide technical leadership for triage, debugging, and automation activities across automotive HPC platforms.
Mentor engineers, lead technical reviews, establish debugging best practices, and drive continuous improvement initiatives across the organization.
Collaborate effectively with internal engineering teams, suppliers, and cross-functional stakeholders to resolve complex system-level issues.