VP, AI Transformation

Responsibilities

• Lead the enterprise AI activation and transformation function, including building and guiding a team responsible for AI strategy, enablement, and execution.
• Establish a long-term vision that balances innovation with responsible adoption.
• Translate enterprise priorities into a clear, actionable AI strategy.
• Identify opportunities to re-engineer business processes using AI, from problem identification through implementation and value realization.
• Balance near‑term productivity gains with longer‑term innovation efforts across a diversified AI portfolio.
• Lead BECU’s internal AI innovation incubator that operates as an internal VC fund, identifying internal opportunities to drive change, funding them, and tracking them as part of the broader AI portfolio.
• Oversee AI governance, including policies, standards and decision frameworks that enable responsible and scalable adoption.
• Partner with leaders across business, technology, and operations to embed AI into real workflows.
• Establish and evolve enterprise AI governance, including policies, standards, and decision frameworks that ensure ethical, compliant, and scalable AI adoption.
• Build organizational capability through education, coaching, and enablement—helping employees develop confidence and fluency in AI tools.
• Influence senior leaders and manage cross‑functional partnerships, ensuring alignment with regulatory expectations, risk tolerance, and member trust.

• Bachelor's degree in computer science, engineering, data science, business, or a related field—or equivalent experience.
• 10+ years of progressive leadership experience across transformation, operations, technology, product, or strategy roles.
• Ability to travel approximately 1–2 times per month, with more frequent travel early on to build relationships, if not based in Seattle.
• Deep technical understanding of AI, including the practical realities of deploying AI in enterprise environments (e.g., in a forward‑deployed or embedded manner), and the ability to engage credibly with technical teams on architecture, data, tooling, implementation constraints, and emerging capabilities.
• Exceptional communication, executive presence, stakeholder management, and problem‑solving skills, with the ability to translate complex AI concepts into practical solutions and effectively engage both technical and non‑technical audiences.