Director, AI Governance & Portfolio
Role details
Job location
Tech stack
Job description
This is a full-time remote position that can be located anywhere in the U.S.
The Director, AI Governance & Portfolio is responsible for establishing and maturing the governance, portfolio management, and operating rhythms that enable responsible, scalable AI adoption across Enlyte. This leader will own the enterprise AI governance framework and the authoritative AI portfolio view, ensuring AI investments are intentional, compliant, measurable, and aligned to business outcomes.
This role will operate within Enlyte's hybrid federated AI model, partnering closely with business-unit AI Catalyst leads, Legal, Compliance, Information Security, Privacy, Finance, data science, engineering, and executive stakeholders. The position begins as a senior individual contributor with a clear trajectory to build and lead a dedicated function as governance and portfolio capabilities mature.
This role begins as a senior individual contributor with trajectory to build and lead a dedicated team as the function matures.
Core Responsibilities:
AI Governance
- Enterprise AI Governance: Mature Enlyte's AI governance framework, including policies, standards, review processes, escalation pathways, and decision forums.
- AI Use Case Lifecycle Management: Evolve the AI use case intake, review, approval, and deployment lifecycle, including stage gates, risk classification, ownership, and accountability structures.
- Responsible AI & Regulatory Readiness: Operationalize responsible AI principles in partnership with Legal, Compliance, Information Security, and Privacy, while translating evolving regulatory expectations into practical controls.
- Enterprise AI Portfolio Management: Maintain and mature a single authoritative view of AI and ML initiatives across business units, lifecycle stages, investment categories, risks, and business outcomes.
- Portfolio Health & Investment Insights: Develop portfolio metrics and reporting that surface ROI, risk concentration, duplication, vendor sprawl, resource constraints, and strategic alignment opportunities.
- Federated Operating Model Enablement: Partner with business-unit AI Catalyst leads to ensure consistent enterprise governance while enabling appropriate business-unit autonomy.
- Executive Strategy & Communications: Provide governance and portfolio insights for AI strategy, OKRs, executive updates, steering committees, and board-level reporting.
- Team Building & Capability Scaling: Build the foundational governance and portfolio function, then support the business case, operating model, and hiring roadmap for a dedicated team.
Requirements
- Education: Bachelor's degree in Computer Science, Data Science, Information Systems, Business, or related field, or equivalent practical experience. Master's degree preferred.
- Governance & Portfolio Expertise: Experience building or operating governance, risk, data, technology, AI/ML, or portfolio management functions.
- AI Risk Framework Fluency: Familiarity with responsible AI practices and frameworks such as NIST AI RMF, ISO 42001, EU AI Act concepts, or similar models.
- AI/ML Lifecycle Understanding: Working knowledge of AI/ML use case frameworks, business case development, delivery concepts, model development, evaluation frameworks, monitoring, drift detection, human oversight, and production readiness.
- Portfolio Tooling & Reporting: Experience with portfolio management tools and practices such as ServiceNow OneTrust, Wrike, or similar platforms preferred.
Leadership & Experience
- Functional Build Experience: 5+ years in technology, data, AI/ML, risk, governance, or portfolio-management roles, with experience building or maturing enterprise capabilities.
- Matrixed Influence: Proven ability to drive alignment across business, technical, legal, compliance, privacy, security, and finance stakeholders without relying solely on direct authority.
- Strategic Execution: Ability to convert ambiguous enterprise needs into practical operating models, governance workflows, reporting rhythms, and measurable portfolio disciplines.
- Regulated Industry Knowledge: Experience in insurance, healthcare, financial services, or another regulated industry is preferred.
- Team Scaling: Experience developing operating models, role definitions, hiring plans, or team structures for new organizational capabilities preferred.
Executive Competencies
- Analytical Rigor: Ability to evaluate AI investments using business value, risk, feasibility, data readiness, operational complexity, and strategic alignment.
- Strategic Communication: Ability to synthesize complex governance, risk, portfolio, and technical information into clear executive narratives.
- Builder Mentality: Comfort operating in ambiguity, creating structure, and personally executing foundational work before a larger team is in place.
- Regulatory Judgment: Ability to translate legal, compliance, and responsible AI expectations into practical governance controls.
- Enterprise Partnership: Collaborative approach to working across federated business units while maintaining enterprise standards and accountability.
Benefits & conditions
We're committed to supporting your ultimate well-being through our total compensation package offerings that support your health, wealth and self. These offerings include Medical, Dental, Vision, Health Savings Accounts / Flexible Spending Accounts, Life and AD&D Insurance, 401(k), Tuition Reimbursement, and an array of resources that encourage a lifetime of healthier living. Benefits eligibility may differ depending on full-time or part-time status. Compensation depends on the applicable US geographic market. The expected base pay for this position ranges from $159,000 - $210,000 annually, and will be based on a number of additional factors including skills, experience, and education.