Principal Engineer, AI Acceleration

설명

About Us

Core IT is responsible for delivering and maintaining the technology, platforms, and services that help teams across GM do their best work. We support product, design, engineering, manufacturing, operations, and corporate functions by improving the tools, workflows, and technology experiences they rely on every day. Our goal is to provide secure, reliable, and seamless technology that helps employees spend less time navigating friction and more time solving the problems that matter most in their domains.

The Role

At General Motors, we are using AI to simplify how work gets done—reducing manual effort, removing friction, and helping engineers and business teams focus on higher-value outcomes.

As a Principal Engineer, AI Acceleration, you will identify high-leverage opportunities, then design, build, and scale AI-powered tools that measurably improve how people work. You will operate at the intersection of software engineering, AI/LLM capabilities, product thinking, and organizational change. This is a hands-on technical leadership role. This isn’t a research or advisory role. You’ll ship tools people use every day and aim for step changes of 10x to 100x, not incremental gains.

For example, our design team’s brand guidelines live in Figma. Instead of maintaining static templates, we built an AI skill that reads the guidelines directly, drafts on-brand presentations, and runs a linter that catches off-brand choices. Work that took days now takes minutes, and the guidelines stay the single source of truth. You’d find and build the next dozen of these.

You will work directly with product, design, engineering, manufacturing, operations, and corporate-function teams to understand the problems behind the requests. You will move quickly from discovery and prototyping to production-quality solutions, while maintaining appropriate standards for security, privacy, reliability, responsible AI, and supportability.

The right person is comfortable creating clarity where there is no specification, switching between executive-level strategy and technical implementation, and measuring success by outcomes.

What You’ll Do

• Find high-leverage opportunities: Embed with teams across GM to identify slow, manual, repetitive, or error-prone work where AI can create a step-change in speed, quality, or user experience.
• Prototype and deliver quickly: Build and test working solutions, validate value with users, and move successful prototypes into reliable, maintainable, supported production capabilities.
• Build on approved platforms: Develop solutions using GM-approved AI and enterprise technologies, integrating with the systems where work already happens, such as Google Workspace, Figma, Jira, enterprise data platforms, and other relevant services.
• Apply strong engineering discipline: Establish appropriate 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: Define success metrics and evaluate time saved, quality, adoption, cycle time, cost, and user satisfaction. Retire or revise solutions that do not produce meaningful outcomes.
• Scale what works: Convert successful implementations into reusable reference architectures, patterns, components, documentation, and enablement that other teams can adopt. Help teams adopt new ways of working and build the capability to extend solutions after initial delivery.
• Provide technical leadership: Mentor engineers, raise the quality bar through design and code reviews, and communicate tradeoffs and recommendations to technical and executive audiences.

Your Skills & Abilities

• 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, not just one or two.
• Strong understanding of LLM application patterns, including prompting, retrieval-augmented generation, 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 keep using them after the initial rollout.
• Strong communication and collaboration skills, with the ability to influence executives, technical experts, and frontline users.
• Comfortable operating with a high degree of autonomy, making decisions with incomplete information, and taking accountability for outcomes.
• A high bar for quality and craft. You care whether the output is actually good, not just whether it runs.

What Will Give You a Competitive Edge

• Experience building internal developer platforms, productivity tools, workflow automation, enterprise AI products, or employee-facing software.
• Experience with agentic systems, Model Context Protocol (MCP), AI skills, orchestration, evaluation frameworks, or multi-model solutions.
• Experience with Glean, Claude, Gemini, Figma AI, Google Workspace, Jira, or comparable enterprise AI and productivity platforms.
• Experience establishing AI engineering standards, reusable patterns, governance, or responsible-use practices in a large organization.
• Experience measuring developer or employee productivity through outcomes such as cycle time, quality, adoption, satisfaction, or cost avoidance.
• Experience mentoring senior engineers and building communities of practice.
• Experience with creative or design workflows, enterprise data systems, or manufacturing and automotive environments.

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.)

이 직무는 재택 기반이지만, 선발된 지원자가 GM 허브에서 특정 거리 이내에 거주하는 경우 주 3회 {또는 관리자가 지정한 다른 빈도로} 출근해야 합니다.

Relocation 지원 혜택은 회사 정책에 따라 자격이 되는 지원자에게 제공됩니다.

다양성 정보

General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다.  자세한 정보는 GM 채용 과정 안내를 참고하십시오.

공평한 취업 기회 선언 (미국)

General Motors는 공평한 기회를 제공하는 고용주임을 자부합니다.  자격을 만족하는 지원자는 인종과 피부색, 성별, 성적 지향, 성별 정체성, 국적, 장애, 재향 군인 보호법 적용 여부와 상관없이 채용 후보로서 심사를 받습니다. 

숙소 (미국 및 캐나다)

General Motors는 장애인을 포함한 모든 구직자들에게 취업 기회를 제공합니다. 구직이나 취업 지원에 도움이 되는 합리적인 숙소가 필요한 경우 [email protected]으로 이메일을 보내시거나 800-865-7580으로 전화주십시오. 이메일에, 귀하가 요청하는 특정한 숙소에 대한 설명과 귀하가 지원하는 직무와 채용 요청서 번호를 포함해주세요.