Chief AI Officer

Job Description Summary

Your role is to lead GE Health Care’s next chapter of AI by scaling enterprise AI capabilities, reusable AI components, and workflow intelligence across products, software, and care pathways. This role focuses on operationalizing AI at enterprise scale – embedding it into regulated environments and enabling hybrid edge/cloud inference across clinical, operational, and enterprise workflows.

You will shape where the company places its AI bets across workflow, reporting, operational intelligence, longitudinal care pathways, automation, SaaS, and enterprise software. Success in this role means translating advances in foundation models, multimodal AI, and agentic systems into measurable outcomes – including improved time-to-decision, operational workflow performance, and longitudinal intelligence – while accelerating AI-enabled software and SaaS growth.

• Define and drive GE Health Care’s enterprise AI strategy, shaping how AI enables product innovation, workflow transformation, enterprise AI architecture, and AI-enabled software and SaaS growth.
• Scale reusable AI capabilities, enterprise services, and common components that create reusable AI leverage across segments and platforms.
• Lead multidisciplinary teams spanning applied science, AI engineering, enterprise architecture, clinical AI strategy, governance, and workflow orchestration.
• Advance modern enterprise AI architecture, including foundation models, multimodal AI, agentic systems, orchestration layers, and enterprise data layers, enabling seamless integration across products and environments.
• Drive enterprise AI lifecycle management and operationalization at scale, including continuous validation, monitoring, deployment, and performance optimization of AI products across installed base and cloud environments.
• Enable hybrid edge/cloud inference strategies that support real-time, reliable AI deployment across devices, software, and clinical workflows.
• Partner across business, product, engineering, regulatory, legal, and operational leaders to embed AI into real-world healthcare environments, improving operational workflow, reporting, and longitudinal care processes.
• Accelerate the transition from standalone AI features to enterprise workflow intelligence that materially improves time-to-decision, operational performance, care coordination, and longitudinal intelligence.
• Establish and uphold enterprise-wide AI governance and Responsible AI frameworks, including regulatory compliance, validation standards, privacy, security, and trust.
• Guide strategic investment decisions to maximize enterprise impact, platform leverage, and differentiated growth.
• Represent GE Health Care externally with regulators, standards bodies, partners, and academic ecosystems to shape the future of healthcare AI.

• Proven executive leadership in artificial intelligence, machine learning, digital health, enterprise software, or a related domain.
• Demonstrated success scaling enterprise AI capabilities into production-grade environments, including hybrid edge/cloud inference and real-world deployment.
• Deep experience across the AI lifecycle, including continuous validation, monitoring, governance, and lifecycle management of AI products across installed base and cloud environments.
• Strong understanding of modern AI systems and enterprise AI architecture, including foundation models, multimodal AI, agentic systems, orchestration, and enterprise data layers.
• Track record of building reusable AI capabilities and shared platforms that drive enterprise leverage across multiple products, segments, or business units.
• Experience translating AI investments into measurable business outcomes, including improvements in time-to-decision, operational workflow, and software/SaaS growth.
• Experience operating within regulated environments, partnering across engineering, product, regulatory, legal, and commercial functions.
• Strong external credibility and engagement across industry, partners, and the broader AI ecosystem.

• Enterprise thinker who connects AI strategy to architecture, workflow, and business outcomes.
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