AI/ML Governance & Automation Lead - Vice President

What you'll do

• Develop and execute comprehensive program plans to accelerate AI/ML model governance and delivery timelines.
• Design scalable governance solutions for agentic, generative, and customer-facing AI/ML use cases.
• Identify and mitigate program risks while implementing contingency plans to maintain delivery momentum.
• Translate complex business, technical, and model risk requirements into actionable execution activities.
• Drive cross-functional alignment on governance standards, controls, and operating procedures for emerging AI capabilities.
• Evaluate program performance and implement data-driven improvements to enhance speed, consistency, and quality.
• Create repeatable frameworks, playbooks, and governance patterns to support scalable AI/ML delivery.
• Communicate program status, risks, and dependencies clearly to senior stakeholders.

What we're looking for

• 5+ years of experience in technical program management leading complex technology, data, AI/ML, risk, or governance programs in a large organization.
• Strong understanding of AI/ML development lifecycles, model governance, model risk management, or related control processes.
• Advanced stakeholder management skills to influence decision-making across engineering, data science, product, risk, and business teams.
• Proven ability to manage complex, cross-functional programs with multiple dependencies, competing priorities, and evolving requirements.
• Demonstrated proficiency in analytical reasoning to break down complex business, technical, risk, and operational objectives into actionable plans.
• Experience driving process improvement, operating model design, or governance transformation in a fast-paced technology environment.
• Strong communication skills to articulate complex technical and governance topics to both technical and non-technical audiences.
• Proven track record of managing resources, timelines, risks, and deliverables in an agile environment.
• Experience with generative AI, agentic AI, large language models, or customer-facing AI/ML solutions (preferred).
• Familiarity with responsible AI principles, model validation, model monitoring, AI controls, or regulatory expectations (preferred).
• Understanding of data management, data governance processes, and related tools (preferred).
• Experience working in financial services, consumer banking, digital product organizations, or highly regulated environments (preferred).
• Experience using approved generative AI tools to automate governance processes and improve efficiency (preferred).