AI Enablement Manager

This is OUR story... and YOUR next chapter
At HCA Healthcare, Digital Transformation & Innovation (DT&I) is accelerating the responsible adoption of Artificial Intelligence to transform healthcare delivery  partner with clinicians, operators, engineers, and data scientists to deploy enterprise‑grade AI solutions that improve patient outcomes, reduce administrative burden, and increase workforce efficiency.
As part of our AI Enablement organization, you will help shape the future of healthcare by delivering AI‑powered products and platforms that move from concept to production and create measurable business and clinical impact. What you will accomplish in this role

As an AI Enablement Manager, you will manage the strategy, roadmap, and execution of enterprise AI products and platform capabilities. Reporting to the Director of AI Enablement, you will lead cross‑functional teams across engineering, architecture, data science, security, governance, and business operations to deliver scalable AI solutions.

This role requires a strong blend of technical expertise, product leadership, and AI deployment experience. You will be responsible for guiding AI products throughout the full lifecycle, from opportunity identification and requirements definition through production deployment, adoption, optimization, and value realization.

• Execute the product strategy and roadmap for Low Code AI, Agentic AI, and AI Enablement capabilities.
• Lead end-to-end AI solution delivery across the product lifecycle including ideation, business case development, MVP delivery, production deployment, scaling, and optimization.
• Translate complex business and clinical problems into technical product requirements, workflows, architecture considerations, and AI‑enabled solutions.
• Partner closely with engineering, architecture, data science, security, and governance teams to deliver secure, scalable, and compliant AI products.
• Drive deployment and adoption of AI solutions in production environments while ensuring operational readiness, monitoring, governance, and business value realization.
• Define KPIs and success metrics for AI products including adoption, operational efficiency, clinical impact, model performance, and ROI.
• Evaluate emerging AI technologies including LLMs, Agentic AI frameworks, multimodal AI, automation technologies, and enterprise AI platforms.
• Prioritize product investments using business value, technical feasibility, risk, and strategic alignment.
• Champion Responsible AI practices including model evaluation, bias mitigation, privacy, security, compliance, and governance.
• Serve as the primary bridge between executive stakeholders and technical delivery teams.

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related technical discipline.
  
  - Required
• 5+ years of Technical Product Management, AI Product Management, Software Product Management, or equivalent experience.
  
  - Required
• Proven experience leading AI solution deployment throughout the full product lifecycle, including development, testing, production implementation, adoption, and optimization.
  
  - Required
• Demonstrated experience delivering enterprise technology products utilizing cloud‑native architectures and modern software engineering practices.
  
  - Required
• Strong understanding of Generative AI, Large Language Models (LLMs), Agentic AI systems, machine learning, and AI‑enabled automation platforms.
  
  - Required
• Experience working with Agile delivery methodologies and product management frameworks.
  
  - Required

• Master's degree in Computer Science, Engineering, Data Science, Business, or related discipline.
• Experience deploying AI solutions in highly regulated industries such as healthcare, finance, or insurance.
• Experience with Google Cloud Platform (GCP), Microsoft Azure, AWS, or enterprise AI platforms.
• Familiarity with MLOps, LLMOps, model monitoring, evaluation frameworks, and AI lifecycle management.
• Experience defining AI governance frameworks, model risk controls, and responsible AI practices.

• Strong technical…