General Motors
Principal Engineer, AI Acceleration
Warren, Michigan, United States of America +1 · Remote/Hybrid · Principal · Full-time · Posted Oct 15, 2026
- Location
- Warren, Michigan, United States of America
Austin, Texas, United States of America - Experience
- 10+ years of progressive software engineering experience; also requires senior technical leadership experience, with no stated duration.
- Visa sponsorship
- GM does not provide immigration-related sponsorship. Candidates who need GM immigration sponsorship now or in the future should not apply.
About the job
Identifies and delivers production AI-powered tools that reduce friction and measurably improve work across GM teams.
What you'll do
- Discover high-impact opportunities, prototype solutions, and move successful tools into supported production.
- Apply engineering, security, privacy, and responsible-AI practices; measure outcomes and scale successful solutions into reusable patterns.
- Provide technical leadership by mentoring engineers, reviewing designs and code, and communicating recommendations to stakeholders.
What they ask for
- 10+ years of progressive software engineering experience, including delivering production software used by customers or employees.
- Experience as a Principal Engineer, senior technical leader, or equivalent, influencing multiple teams or organizations.
- Hands-on experience building AI- or LLM-enabled applications, agents, or automations across a range of AI tools and models.
- Strong understanding of LLM application patterns and experience integrating AI solutions with enterprise applications, APIs, data sources, identity systems, and workflow platforms.
Nice to have
- Experience with agentic systems, Model Context Protocol (MCP), AI skills, orchestration, evaluation frameworks, or multi-model solutions.
- Experience with enterprise AI and productivity platforms such as Glean, Claude, Gemini, Figma AI, Google Workspace, or Jira.
Tools
LLM, APIs, distributed systems, CI/CD, Google Workspace, Figma, Jira, Model Context Protocol (MCP)
AI focus
Build and scale AI- and LLM-powered tools, agents, and automations for employee productivity; apply responsible-AI practices, evaluate impact, and help teams adopt AI.
Model-written summary · the original posting is authoritative