Senior Product Director, Enterprise AI R&D

GE HEALTHCARE•Waukesha, WI

55d

About The Position

The Enterprise AI R&D Product Director will lead GE HealthCare’s enterprise-wide efforts to define, govern, and execute the roadmap for AI-driven transformation in Research & Development and Quality. This role integrates strategy, product leadership, cross-functional alignment, and value delivery to accelerate innovation, reduce cycle time, and maximize enterprise benefit.

Requirements

Bachelor's or advanced degree in engineering, computer science, or related technical field.
12+ years of industry experience with at least 6 years leading complex cross-functional initiatives.
Expertise in AI/ML technologies including LLMs, RAG, validation methods, and responsible AI practices.
Strong understanding of regulated R&D processes, Design Controls, and Quality Management Systems.
Proven success in product management, program leadership, or technical portfolio governance.
Experience quantifying business value, defining ROI, and driving measurable outcomes.

Nice To Haves

Exceptional communication, storytelling, and executive influence skills.
Experience designing or deploying enterprise AI platforms or complex digital ecosystems.
Strong systems-thinking approach with ability to model workflows and identify AI leverage points.
Ability to lead through ambiguity and build alignment across distributed teams.

Responsibilities

Own and maintain the enterprise roadmap for AI in R&D and Quality, ensuring alignment with the company’s AI Big Bets.
Strengthen organizational alignment by delivering clear and timely communications that help leaders understand strategic direction and progress while keeping the broader organization informed of key objectives and outcomes.
Stay current on AI, regulatory, and industry trends to guide prioritization and strategic investment, helping the business anticipate change, mitigate risk, and capitalize on emerging opportunities.
Partner with Quality, Segments, STO, and IT to define scope, benefits, and requirements for enterprise priority initiatives, ensuring investments are aligned, resourced appropriately, and positioned to deliver measurable business value.
Translate business and engineering needs into clear definitions of value, scope, requirements, and “ready” criteria.
Define and maintain the definition of “ready” for AI tools, ensuring alignment with validation, governance, and QMS expectations.
Drive measurable productivity gains and EBIT impact through disciplined sequencing of AI use cases.
Engage champion segments to pilot, refine, adopt, and scale validated AI solutions, ensuring operational sponsorship, accelerating learning cycles and reducing risk ahead of broader enterprise deployment.
Act as a constant communicator—upward, downward, and across—ensuring alignment, transparency, and momentum.
Maintain a healthy funnel of new AI use case opportunities, partnering across the enterprise to identify, assess, and prioritize, which enables disciplined investment and maximizes return on AI innovation.
Ensure compliance with Responsible AI, cybersecurity, privacy, and GxP validation frameworks, safeguarding product quality and patient safety and ensuring all AI solutions meet the highest industry and regulatory standards.
Communicate benefit realization, adoption progress, and risk mitigation to executive stakeholders, strengthening accountability and helping leadership prioritize resources toward the highest‑value initiatives.