About the position:

We’re looking for an AI Governance & Enablement Lead to drive safe, responsible, and widespread AI adoption across Definitive Healthcare. You will build the governance framework that gives teams clear guardrails, and the enablement programs that turn AI into measurable business value. You’ll partner with legal, privacy, compliance, security, IT, data, and business teams to turn complex risk into practical policy.

This role isn’t about creating barriers. It’s about making the safe way the easy way, so every teammate can use AI effectively and every AI initiative can move from idea to production quickly and responsibly. Strong governance and confident, well-trained teams are what let us move fast on AI without putting customer trust at risk.

What You’ll Do

AI adoption and enablement

• Own the enterprise AI enablement strategy and roadmap. Set adoption goals and success metrics, such as active users, time saved, use cases delivered, and business impact, and report progress to senior leadership.
• Partner with business leaders to identify high-value AI use cases and remove barriers to adoption.
• Design and deliver role-based AI literacy, training, and certification programs for employees, managers, and engineering teams.
• Build and lead an AI Champions network across departments to share best practices, surface needs, and scale adoption peer to peer.
• Maintain an approved AI tool and model catalog, along with reusable playbooks, prompt libraries, templates, and reference architectures.
• Create sandboxes and fast-track routes so teams can safely experiment, pilot, and scale AI solutions.
• Lead change management and communications that build trust, address concerns, and sustain adoption.

AI governance and Responsible AI

• Direct the design, launch, and ongoing operation of a centralized AI Trust Center that serves as the single source of truth for AI policies, approved tools, and guidance.
• Build a streamlined intake and evaluation framework to assess, tier, and approve predictive, generative, and agentic AI initiatives based on business value, technical readiness, and risk, with clear turnaround times.
• Define and enforce Responsible AI standards to measure and reduce algorithmic bias, hallucination, security threats, and intellectual property leakage.
• Establish governance across the full AI/ML lifecycle, including data sourcing, model training and fine-tuning, testing and evaluation, deployment, and production monitoring.
• Set usage guardrails for foundation models, third-party AI tools, and multi-agent Agentic AI systems, including human-in-the-loop requirements.
• Set AI vendor and third-party risk assessment standards with security, procurement, and legal.
• Ensure adherence to global AI regulations and risk frameworks, such as the EU AI Act, NIST AI Risk Management Framework, and ISO/IEC 42001. Turn legal requirements into automated, scalable technical controls.
• Lead an AI governance council and maintain an AI inventory and risk register to keep the company audit-ready.

Data foundations for AI

• Partner with data and engineering teams so AI is built on governed, high-quality, well-classified data, including standards for classification, cataloging, lineage, quality, and observability.
• Serve as the functional governance owner for Databricks, using Unity Catalog for centralized access management, lineage, and auditable data sharing.
• Govern data access and compliance policies for data used in model training, vector search, and Retrieval Augmented Generation (RAG) solutions.

What Success Looks Like

• Teammates across every department use approved AI tools with confidence, and adoption targets are met or exceeded.
• New AI use cases move from intake to decision within a defined, published turnaround time.
• The AI Trust Center is the first stop for AI policies, approved tools, and guidance.
• The company stays audit-ready against the EU AI Act, the NIST AI Risk Management Framework, and internal policy, with no material AI-related incidents.
• Governed data in Databricks supports AI use cases from training through production.

What You’ll Bring

• 10+ years of experience in AI governance, data governance, risk and compliance, or technology enablement, with a progressive track record of leading enterprise-scale programs.
• Bachelor’s or Master’s degree in Computer Science, Information Management, or a closely related quantitative or technical discipline, or equivalent experience.
• Proven success driving adoption of new technology across a large organization, including training, change management, and measuring outcomes.
• Clear conceptual and functional understanding of LLMs, Generative AI, Agentic AI, vector search, and secure RAG architectures.
• Deep familiarity with modern data privacy and AI regulations and risk frameworks, with a proven ability to turn legal and policy requirements into practical, automated guardrails.
• Hands-on experience governing data in Databricks, including Unity Catalog for lineage and access management.
• Exceptional communication, influence, and stakeholder management skills, with the ability to partner credibly with executives, legal, security, and technical teams.
• Preferred: experience building governance bodies, intake processes, and operating models that balance speed with control.

Compensation and Benefits:

The salary range for this position is $129,000– $241,000 per year, which represents the base pay the company reasonably and in good faith expects to pay for this role. Actual pay within this range will be determined based on factors such as relevant experience, skills, and qualifications. 

Depending on the position, employees may also be eligible to participate in a company bonus or commission plan. All employees are eligible for a comprehensive benefits package, including medical, dental, and vision coverage, flexible paid time off, and participation in the company’s 401(k) plan with employer contribution.