AI Transformation Leader

MiniMed•Duluth, GA

1d•Onsite

About The Position

The AI Transformation Leader is responsible for driving enterprise wide adoption of Artificial Intelligence by aligning strategy, governance, and technology to accelerate business value. This leader partners across functional, commercial, and technical teams to embed responsible, scalable AI into business processes, and operating models. The role brings a blend of strategic vision, change leadership, and technical fluency, to ensure AI initiatives deliver measurable outcomes and are adopted sustainably across the organization.

Requirements

10+ years in digital transformation, enterprise technology, AI/ML leadership, or equivalent strategic roles.
Experience leading large scale, cross functional transformation in complex global organizations.
Executive presence with the ability to influence, challenge, and inspire at all organizational levels.
Strong understanding of AI/ML concepts, GenAI, agentic AI architectures, automation frameworks, and modern cloud platforms.
Familiarity with data governance, model lifecycle management, AI risk frameworks, and model monitoring.
Experience working with product, engineering, or architecture teams to build AI powered solutions.
Proven ability to manage multi workstream transformation programs and drive adoption at scale.
Strong skills in organizational change management, training strategy, and internal communications.
Experience building and scaling literacy or upskilling programs.
Ability to translate AI potential into tangible business value.
Strong judgment on prioritization, resource allocation, and ROI evaluation.
Experience engaging with senior executives and navigating matrixed organizations.
Exceptional communication, facilitation, and influence skills.
Ability to cultivate strategic partnerships across commercial, technical, and operational domains.
High emotional intelligence and adaptability in a fast evolving technology landscape.

Nice To Haves

Master's degree in business, engineering, computer science, data science, or related field.
Experience in highly regulated industries (e.g., healthcare, finance).
Experience with AI governance or responsible AI frameworks.
Prior experience designing or leading AI Center of Excellence (COE) structures.

Responsibilities

Define the enterprise AI vision, strategic priorities, and multi year transformation roadmap.
Evaluate emerging AI technologies (e.g., GenAI, autonomous agents, analytics, agentic architectures) and identify high value business use cases.
Partner with business and technology leaders to prioritize investments, ensure alignment to enterprise strategy, and track measurable outcomes.
Act as the connective tissue between technical teams and business functions, ensuring AI implementations address real business needs.
Track value realization, quantify impact on productivity, cost, patient and provider experience, and revenue—socializing wins across the enterprise.
Lead development and ongoing refinement of AI governance frameworks, including risk management, compliance, transparency, and responsible use principles.
Partner with legal, data privacy, security, and regulatory teams to ensure safe, compliant deployment of AI systems across markets and product lines.
Establish decision making bodies, review cycles, and audit processes for AI model performance and adoption.
Build and scale AI literacy programs that improve workforce fluency across technical and non technical roles.
Develop learning pathways, training programs, and continuous education to support AI adoption at scale.
Partner with HR, functional leaders, and Learning & Development to embed AI competencies into role design, performance expectations, and talent strategy.
Oversee cross functional delivery of enterprise AI capabilities, including automation frameworks, agent based solutions, orchestration engines, and cloud based AI services.
Partner with engineering, data, and architecture teams to develop scalable AI systems integrated into core business processes and platforms.
Support enterprise integration patterns (APIs, MCP frameworks, data pipelines, model monitoring) ensuring reliability, security, and enterprise grade performance.
Craft compelling narratives, communication plans, and storytelling that build trust and drive enthusiasm for AI adoption.
Partner with executives and internal communications teams to amplify success stories, clarify expectations, and demystify AI capabilities.
Lead organizational change management practices to ensure successful rollout and sustained adoption.