AI Governance

About the role

Since 1973, East West Bank has served as a pathway to success. With over 110 locations across the U.S. and Asia, we are the premier financial bridge between the East and West. Our teams of experienced, multi-cultural professionals help guide businesses and community members on both sides of the Pacific looking to explore new markets and create new opportunities, and our sustained growth and expertise in industries like real estate, entertainment and media, private equity and venture capital, and high-tech help build sustainable businesses and expand our associates’ potential for career advancement. Headquartered in California, East West Bank (Nasdaq: EWBC) is a top-performing commercial bank with a strong foundation, an enterprising spirit and a commitment to absolute integrity. East West Bank gives people the confidence to reach further.

East West Bank is seeking a highly experienced AI Governance to lead the design, implementation, and operationalization of the bank’s enterprise AI governance framework. This role is designed for a hands-on governance leader with deep expertise in AI governance, data governance, risk management, and regulatory compliance within highly regulated industries. The ideal candidate combines practical implementation experience with strong understanding of AI/ML technologies, enterprise controls, data risk, model risk, operational governance, and responsible AI practices. The role will partner across business, technology, data, legal, risk, compliance, audit, and operations teams to establish scalable governance processes supporting AI use cases from intake through production monitoring and enterprise adoption. This position is part of East West Bank’s Enterprise AI Strategy & Transformation organization, focused on scaling AI initiatives into governed, measurable, compliant, and enterprise-ready capabilities.

Responsibilities

• Lead the design and implementation of the enterprise AI governance framework, operating model, standards, controls, and governance processes.
• Establish and operationalize governance processes for AI intake, inventory management, prioritization, risk assessment, technology gating, approval workflows, monitoring, issue remediation, and value realization tracking.
• Drive governance activities across the full AI lifecycle including ideation, proof of concept, pilot, production deployment, monitoring, model review, and retirement.
• Partner with business, technology, data, legal, risk, compliance, cybersecurity, and audit teams to ensure AI initiatives align with enterprise governance standards and regulatory expectations.
• Define governance controls for AI-enabled solutions including data quality, lineage, privacy, explainability, human oversight, auditability, retention, access governance, and operational resiliency.
• Establish AI governance reporting, dashboards, metrics, and executive-level transparency related to AI adoption, business value, risk exposure, control effectiveness, and remediation progress.