Robotics AI Strategy & Program Lead, Early Career

Job Description

About the role

General Motors is building one of the most ambitious AI and robotics programs in manufacturing, developing systems capable of autonomously manipulating thousands of parts across GM’s global plant network. Our Robotics AI organization sits at the intersection of AI research, robotics, manufacturing engineering, and AI product management, driving both cutting‑edge technology and real factory impact.

We are looking for a Robotics AI Strategy & Program Lead who can own end‑to‑end, cross‑functional initiatives that cut across AI research, robotics engineering, data infrastructure, and manufacturing operations. They will be known as an operator who gets things done across complex organizations.

This role blends strategy, program management, analytics, and hands‑on AI tools work: you will structure the problems, build the dashboards, dive into the data, leverage and build AI agents, and drive large programs to completion while unblocking teams across IT, Purchasing, Vendors, Finance, HR, and Manufacturing.

You will be embedded with AI researchers, roboticists, AI engineers, data engineers, and AI product managers, translating between technical and non‑technical stakeholders and ensuring that what we build is strategic, measurable, and shippable - from fast-turnaround experiments to multi-year platform bets.

What you will own

Program and project leadership

- 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 tool rollouts) with clear milestones, owners, and success metrics.

- Build and maintain program roadmaps, dependency maps, and risk registers; proactively identify and resolve blockers across teams.

- Drive operating rhythms (standups, reviews, steering forums) with AI Research, AI Engineering, Robotics Engineering, Manufacturing Engineering, and AI Product Management.

- Roll up your sleeves to push work through organizational and process complexity—coordinating with IT, Purchasing, Vendors, Finance, HR, and other partners to keep programs moving.

- Comfortably manage multiple initiatives at once, switching contexts between short-turnaround deliverables and long-horizon programs without dropping details

Strategy, storytelling, and decision support

- Partner with leadership to define and refine Robotics AI strategy, including problem selection, sequencing of bets, and success metrics.

- Structure clear narratives and storyboards that connect technical work to GM‑level business outcomes and manufacturing KPIs.

- Prepare executive‑ready presentations and decision docs (SVP and above), highlighting what has changed, what is at risk, and what decisions are needed.

- Translate complex technical options into simple, structured trade‑off frameworks for senior decision‑makers.

Data, analytics, and tooling

- Go deep on data: define questions, shape logging/telemetry requirements, pull and analyze data using SQL, Python, or R, and translate findings into actionable insights.

- Build and maintain dashboards (e.g., Looker, Power BI) that track program KPIs, model and system performance, factory deployment health, and operational metrics.

- Partner with Data Engineering and platform teams to leverage Databricks and other infrastructure for analytics and reporting.

- Design and orchestrate GenAI‑powered workflows and agents to automate repetitive analysis, reporting, and operational tasks where appropriate.

- Continuously learn and adopt new AI, data, dashboarding, and tracking tools, and help the broader team do the same

AI, robotics, and technical collaboration

- Act as a fluent technical partner to AI researchers, robotics engineers, and data engineers—you don’t need to write production code or models, but you do need to understand what makes them hard.

- Help ensure that data collection, labeling, evaluation, and deployment workstreams are aligned with program goals and success metrics.

- Collaborate closely with AI product managers to connect user needs, technical capabilities, and deployment constraints, especially in manufacturing settings.

- Engage with external partners and vendors in AI, robotics, and data tooling where both technical depth and program context are required.

Ways of working and culture

- Champion a learning‑oriented culture: rapidly explore new tools (GenAI, agents, analytics, low‑code platforms), techniques, and methodologies, and help the team adopt what works.

- Model “get your hands dirty” execution—whether that’s pulling data, building a quick dashboard, prototyping an AI agent, or refining a deck the night before an exec review.

- Help continuously improve our program management, measurement, and communication practices across the Robotics AI org.

- Practice proactive, “over-communication” with leaders and stakeholders—keeping partners up to speed on risks, decisions, and progress, and responding quickly to questions or asks.

- Thrive in a dynamic environment where priorities can shift, and enjoy moving between strategic problem framing, detailed data work, and day-to-day execution.

Required qualifications

- MBA with previous engineering or technical experience or Master's in Computer Science, Electrical Engineering, Mechanical Engineering, or a closely related technical field.

- 2-4 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, or similar), ideally at the intersection of AI and robotics.

- Demonstrated ability to lead large, complex cross‑functional programs with high ambiguity and multiple parallel workstreams.

- Strong strategic thinking and storytelling skills: can frame problems, structure options, and communicate clearly to both technical and non‑technical audiences.

- Comfort operating as a hands‑on analyst and builder, including:

- Writing SQL and using Python or R for analysis

- Building dashboards in tools like Looker or Power BI

- Working in Databricks and similar data platforms

- Demonstrated fluency with GenAI tools (e.g., prompt engineering, using copilots/assistants in daily workflows) 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 application platforms (e.g., Power Apps, AppSheet).

- Ability to modulate communication style: comfortable diving into technical details with AI researchers and roboticists, and equally comfortable presenting synthesized insights to senior, non‑technical executives.

- Proven cross‑functional collaboration and influence skills; known as a team player who creates clarity and momentum rather than just tracking tasks.

- Demonstrated experience working directly with technical teams (AI researchers, AI engineers, roboticists, data engineers), understanding their work well enough to track progress, surface risks, and offer hands-on support

Preferred Qualifications

- Prior work in robotics, robotics AI, or physical AI systems, especially in manufacturing, industrial, or logistics environments.

- Experience operating at the intersection of research and production, helping teams balance exploration with delivery.

- Background in data‑driven decision‑making, experimentation, and KPI design in complex technical domains.