Manager, Software Engineering

General Motors is seeking a Manager, Software Engineering to enhance the quality and operational efficiency of its simulation tests and protocols. This role involves leading a team to build scalable infrastructure, influence technical roadmaps, and mentor engineers while driving cross-functional collaboration on software development standards.

Responsibilities:

• Build highly scalable infrastructure and automations to empower large-volume test creation, full-lifecycle health monitoring, and process improvements
• Effectuate scalable quality assessments and automations empowering better consistency, and process codifications to increase confidence in offshore vendor team and automated output
• Influence technical roadmaps and strategic priorities while partnering cross-functionally to identify and resolve efficiency pain points from team members and customers
• Write software in a relatively new vertical unconstrained by legacy bloat
• Leverage AI tools (e.g., code assistants, automated test generation, analytics) to boost productivity, code quality, and innovation in simulation testing
• Uphold high code quality and architecture standards through code reviews and technical leadership, including providing mentorship to other engineers on simulation testing and software best practices
• Mentor and uplevel reports and colleagues to uplevel their software engineering skills (primarily Python). Implement best practices for design, testing, and reviews. Provide and inspire in-depth design and code reviews
• Leading performance management, review cycles, and hiring processes for the team

Requirements:

• BS, MS, or PhD in Computer Science, Engineering, or equivalent experience
• 8+ years of experience developing scalable software solutions using Python in a production environment
• Proven experience in building backend infrastructure supporting internal tooling and dashboards
• Strong communication and collaboration skills
• Experience supporting autonomy, ADAS, robotic, or complex simulation systems
• Experience using or integrating AI-powered development tools (e.g., GitHub Copilot, Cursor) for code generation
• Demonstrated ability to drive technical design and execution across multiple teams and organizations in a remote or distributed environment, maintaining a high bar for system design clarity and comprehensive technical documentation
• Familiarity with SQL, BigQuery, time-series data analysis, performance monitoring tools, and dashboarding systems (e.g., Looker, Streamlit)
• Knowledge of data orchestration tools (Airflow, DBT), and event-driven system design
• Familiarity with machine learning data operations, test quality frameworks, or simulation validation workflows
• Comfort asking hard questions, challenging assumptions, and advocating for quality and rigor