AI Incubation Manager

Manager Of The Ai Incubation Team

Required Skills & Experience

• Master's degree in related field – Artificial Intelligence, Data Science, etc

• 3-5 years of leadership in AI, ML, data science, research engineering, or innovation

• Experience with Python and Cobra

• Experience in an Azure environment

• Hands on experience supporting AI projects, prototyping, data analysis, or early stage concept development

• Leadership – ability to lead 5-6 technical contributors (data scientists or ML engineers)

• Ability to communicate with high level stakeholders

Job Description

Insight Global is seeking a Manager of the AI Incubation Team for a large academic health facility in the Southeast. This leader will lead the rapid experimentation and prototype development function for the Center of Artificial Intelligence. This role enables departments with novel AI concepts to receive technical support they cannot execute alone due to resource, skill, or infrastructure limitations. The manager drives early stage innovation, assesses feasibility, develops prototypes, and transitions validated concepts into enterprise deployment pathways.

Responsibilities

• Concept Intake, Evaluation & Prioritization – 30%

• Assess AI ideas for business value, feasibility, and alignment with health system priorities.

• Develop a structured prioritization framework for incubation candidates.

• Lead concept scoping and definition for new AI initiatives.

• Incubation Team Leadership – 25%

• Manage a team of Junior Data Scientists and ML Engineers.

• Balance resources across multiple incubation projects.

• Promote a culture of innovation and experimentation.

• Prototype Development & Technical Oversight – 25%

• Oversee feasibility assessments, rapid prototyping, validation, and data review.

• Ensure responsible, ethical, and compliant AI development.

• Document technical frameworks and deployment-readiness criteria.

• Transition to Deployment & Stakeholder Integration – 15%

• Partner with Strategy & Ops and Clinical Data teams to transition validated prototypes.

• Deliver design documentation, implementation guidance, and risk assessments.

• Innovation Leadership & Enterprise Impact – 5%

• Maintain a pipeline of emerging AI opportunities across the health system.

• Drive innovation in applied healthcare AI.

• Advance patentable ideas into implementation and potential royalty-generating solutions.

Key Annual Performance Objectives

• Deliver 2–3 validated AI innovations annually (deployed, validated, or patentable).

• Expand internal capacity for early-stage AI exploration.

• Reduce barriers to pursuing high-impact AI initiatives.