Principal Engineer, AI Acceleration
Salary not listed • Warren, Michigan, United States of America • Full-time
Posted 16d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Job Location
Warren, Michigan, United States of America
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
General Motors is leveraging AI to streamline work processes, reduce manual effort, and enable engineers and business teams to focus on higher-value outcomes. As a Principal Engineer, AI Acceleration, you will identify impactful opportunities and then design, build, and scale AI-powered tools that significantly improve how people work. This is a hands-on technical leadership role focused on shipping tools that deliver substantial improvements, not just incremental gains. You will collaborate directly with various teams across the company to understand their challenges, moving from discovery and prototyping to production-quality solutions while adhering to standards for security, privacy, reliability, responsible AI, and supportability. The ideal candidate can create clarity from ambiguity, balance strategic thinking with technical implementation, and measure success by tangible outcomes.
Responsibilities
- Identify high-leverage opportunities where AI can create step-change improvements in speed, quality, or user experience by embedding with teams across GM.
- Prototype and deliver working AI solutions quickly, validate their value with users, and transition successful prototypes into reliable, maintainable, and supported production capabilities.
- Develop solutions using GM-approved AI and enterprise technologies, integrating with existing systems like Google Workspace, Figma, and Jira.
- Apply strong engineering discipline, establishing practices for requirements, architecture, testing, observability, security, privacy, access control, deployment, incident response, and lifecycle management.
- Partner with security, legal, privacy, and risk stakeholders to set practical guardrails for safe and responsible AI use.
- Measure business impact by defining success metrics and evaluating time saved, quality, adoption, cycle time, cost, and user satisfaction, retiring or revising solutions that don't produce meaningful outcomes.
- Scale successful implementations into reusable reference architectures, patterns, components, documentation, and enablement for adoption by other teams.
- Provide technical leadership through mentoring engineers, raising quality standards via design and code reviews, and communicating tradeoffs and recommendations to technical and executive audiences.
Requirements
- 10+ years of progressive software engineering experience, including delivery of production software used by real customers or employees.
- Demonstrated experience serving as a Principal Engineer, senior technical leader, or equivalent role with influence across multiple teams or organizations.
- Hands-on experience designing and building AI- or LLM-enabled applications, agents, or automations across a wide range of AI tools and models.
- Strong understanding of LLM application patterns, including prompting, retrieval-augmented generation (RAG), tool use, context management, model selection, evaluation, and observability.
- Experience integrating AI solutions with enterprise applications, APIs, data sources, identity systems, and workflow platforms.
- Strong software engineering fundamentals, including architecture, APIs, distributed systems, testing, CI/CD, monitoring, security, and operational excellence.
- Ability to translate ambiguous business problems into clear product and technical strategies, then deliver working solutions through iterative development.
- Demonstrated ability to use data and user feedback to prioritize work and evaluate adoption, quality, and measurable impact.
- Demonstrated success helping people and teams adopt AI tools and continue using them after the initial rollout.
- Strong communication and collaboration skills, with the ability to influence executives, technical experts, and frontline users.
- Comfort operating with a high degree of autonomy, making decisions with incomplete information, and taking accountability for outcomes.
- A high bar for quality and craft.