Robotics AI Strategy & Program Lead

General Motors•Warren, MI

2d•Hybrid

About The Position

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. We are seeking a Robotics AI Strategy & Program Lead to own end-to-end, cross-functional initiatives spanning AI research, robotics engineering, data infrastructure, and manufacturing operations. This role blends strategy, program management, analytics, and hands-on AI tooling: you will structure problems, drive roadmaps, build dashboards, dive into data, leverage and design AI agents, and lead large programs to completion. You will work day-to-day with AI researchers, roboticists, AI engineers, data engineers, and AI product managers, translating between technical and non-technical stakeholders to ensure we build solutions that are strategic, measurable, and shippable.

Requirements

Bachelor’s or higher degree in Computer Science, Electrical Engineering, Mechanical Engineering, or a closely related technical field.
6+ years of experience in one or more of: Management consulting or corporate strategy, Product management or technical program management, Data science or data analytics
Meaningful experience in AI, ML, or robotics (e.g., robotics AI, applied ML, computer vision, intelligent automation).
Proven ability to lead large, complex cross-functional programs with high ambiguity and multiple parallel workstreams.
Strong strategic thinking and storytelling skills; able to frame problems, structure options, and communicate clearly to technical and non-technical audiences.
Hands-on experience: Writing SQL and using Python or R for analysis
Building dashboards in tools like Looker or Power BI
Working in Databricks or similar data platforms
Demonstrated fluency with GenAI tools (e.g., prompt engineering, copilots/assistants) and a track record of designing or orchestrating AI-assisted workflows or agents.
Experience with modern collaboration and delivery tooling such as Jira and low/no-code platforms (e.g., Power Apps, AppSheet).
Ability to modulate communication style: comfortable in deep technical discussions with AI researchers and roboticists, and equally comfortable presenting synthesized insights to senior, non-technical executives.
Strong cross-functional collaboration and influence skills; known as a team player who creates clarity and momentum, not just tracks tasks.

Nice To Haves

Experience in robotics, robotics AI, or physical AI systems, especially in manufacturing, industrial, or logistics settings.
Experience operating at the research–production intersection, helping teams balance exploration with delivery.
Background in data-driven decision-making, experimentation, and KPI design in complex technical domains.
Experience defining and instrumenting metrics for AI or robotics systems (e.g., reliability, coverage, cycle time, throughput, data quality).
Comfort with storyboarding and narrative design; you naturally think in terms of “what’s the story?” and how to land it in a deck or memo.
Track record of rapidly learning new technical domains and tools and helping teams adopt them effectively.

Responsibilities

Own end-to-end cross-functional projects from problem framing and strategy through execution, measurement, and iteration.
Program manage large, multi-team initiatives (e.g., new robotics AI capabilities, data/telemetry programs, analytics or tooling rollouts) with clear milestones, owners, and success metrics.
Build and maintain program roadmaps, dependency maps, and risk registers; proactively identify and resolve blockers.
Drive operating rhythms (standups, reviews, steering forums) across AI Research, AI Engineering, Robotics Engineering, Manufacturing Engineering, and AI Product Management.
Partner with leadership to define and refine Robotics AI strategy, including problem selection, sequencing of bets, and success metrics.
Create clear narratives that connect technical work to GM-level business outcomes and manufacturing KPIs.
Prepare executive-ready presentations and decision docs (SVP and above), highlighting changes, risks, and required decisions.
Translate complex technical options into simple, structured trade-off frameworks for senior decision-makers.
Define questions, shape logging/telemetry requirements, pull and analyze data using SQL and Python or R, and turn findings into actionable insights.
Build and maintain dashboards (e.g., Looker, Power BI) tracking program KPIs, model/system performance, deployment health, and operational metrics.
Partner with Data Engineering and platform teams to leverage Databricks or similar platforms for analytics and reporting.
Design and orchestrate GenAI-powered workflows and agents to automate repetitive analysis, reporting, and operations where appropriate.
Act as a fluent technical partner to AI researchers, robotics engineers, and data engineers; you don’t need to ship production code, but you understand what makes these systems hard.
Ensure data collection, labeling, evaluation, and deployment workstreams are aligned with program goals and success metrics.
Collaborate with AI product managers to connect user needs, technical capabilities, and deployment constraints, especially in manufacturing environments.
Engage external partners and vendors in AI, robotics, and data tooling where both technical depth and program context are required.
Champion a learning-oriented, experimentation-driven culture: rapidly explore new tools (GenAI, agents, analytics, low-code platforms) and help the team adopt what works.
Model hands-on execution—pulling data, building quick dashboards, prototyping agents, and refining decks as needed.
Continuously improve program management, measurement, and communication practices across the Robotics AI organization.