Manager, AI Strategy & Deployment

The Manager of AI Strategy and Deployment leads the people, processes, and technical delivery behind Tampa General Hospital's artificial intelligence and machine learning initiatives. Sitting within the Office of the Chief Medical Informatics and AI Strategy Officer and reporting to the Associate Chief Medical Informatics and AI Strategy Officer, this leader is accountable for taking AI capabilities from concept and validation through safe, governed, and durable deployment into clinical and operational workflows -- including tools built in-house, embedded in the EHR, and acquired from vendors. This is a hands-on leadership role. The manager builds and directs a multidisciplinary team, partners closely with clinical, operational, IT, data governance, compliance, and research stakeholders, and ensures that every model in production is monitored, validated, equitable, and aligned with institutional and regulatory expectations. This role is responsible for performing job duties in accordance with the mission, vision, and values of Tampa General Hospital.

Essential Functions:

• Lead, coach, and develop a cross-functional team of software engineers, EHR analysts, data scientists, product managers, and project managers while establishing role clarity, performance expectations, and career development pathways.
• Oversee TGH's AI portfolio, including predictive analytics, generative AI tools, ambient documentation, clinical decision support, operational automation, and virtual care solutions.
• Direct the end-to-end AI deployment lifecycle, including intake, prioritization, solution design, integration, validation, implementation, monitoring, and ongoing optimization.
• Translate organizational AI strategy into an executable roadmap, aligning resources, priorities, timelines, and outcomes with the goals of the Office of the Chief Medical Informatics and AI Strategy Officer.
• Partner with governance, compliance, legal, privacy, clinical, and data leadership teams to ensure AI solutions meet safety, ethical, regulatory, and institutional standards.
• Establish and maintain AI monitoring and evaluation programs, including oversight of model performance, bias, equity, adoption, safety metrics, and continuous improvement initiatives.
• Lead EHR and technical integration efforts, ensuring AI capabilities are securely and effectively embedded within Epic, virtual care platforms, clinical workflows, and enterprise technology ecosystems.
• Oversee AI-enabled virtual care initiatives, including telehealth, remote patient monitoring, virtual nursing, virtual triage, and other digital health programs to improve patient access and care delivery.
• Serve as the primary operational liaison between clinical leadership, IT, research, governance bodies, business stakeholders, and external vendors, providing direction on prioritization, delivery, risks, and change management.
• Measure and communicate portfolio performance and value realization, leveraging outcome, operational, quality, safety, and adoption metrics to inform decision-making and strategic investment priorities.
• Master's Degree Health Informatics or Biomedical Informatics
• Master's Degree Computer Science, Data Science, or Engineering
• Master's Degree Healthcare Administration (MHA) or Business (MBA)
• Master's Degree Related Field
• Board certification in Clinical Informatics for clinician candidates

Experience Qualifications:

• Five (5) years of progressive professional experience in health IT, clinical informatics, data science, or software delivery, including work with AI/ML or analytics in a healthcare setting, with at least two (2) of those years in a formal Leadership role.
• Demonstrated success deploying and managing AI, analytics, or technology solutions in a clinical environment.

Skills and Abilities:

• Bridging translator -- moves fluently between clinical, technical, and executive audiences.
• Judgment under uncertainty -- makes sound safety-vs-speed tradeoffs and knows when to escalate; operates comfortably and effectively in ambiguity.
• Operational rigor -- brings structure, documentation, and accountability to complex, multi-stakeholder delivery; develops and operates within budget parameters.
• Responsible AI mindset -- treats equity, transparency, and ongoing monitoring as core requirements, not afterthoughts.
• People-first leadership -- develops talent and builds a cohesive team from diverse technical specialties; creates effective relationships and collaborates at all levels across the TGH system.