AI Governance

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.

• 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.
• Lead governance processes related to LLM, Generative AI, RAG, intelligent automation, and advanced analytics solutions.
• Evaluate AI technologies, platforms, and vendors to ensure alignment with enterprise architecture, security, compliance, operational, and risk standards.
• Support regulatory, audit, model risk, and enterprise risk management activities related to AI and advanced analytics environments.
• Translate governance policies into repeatable operational procedures, evidence requirements, controls, checklists, and implementation standards.
• Promote enterprise AI governance awareness, adoption, and responsible AI practices across business and technology organizations.
• Perform other duties as assigned.

• 8+ years of experience in AI governance, data governance, model risk, enterprise risk, compliance, data management, or related governance disciplines within financial services, fintech, insurance, or other highly regulated industries.
• Strong hands-on experience designing and implementing enterprise AI governance frameworks and operational governance processes in production environments.
• Demonstrated experience operationalizing AI governance across AI intake, inventory management, prioritization, technology assessment/gating, risk assessment, approvals, monitoring, remediation, and value/metrics reporting.
• Deep understanding of AI risk, model risk, data risk, operational risk, privacy, explainability, bias, human oversight, and responsible AI principles.
• Strong understanding of regulatory, compliance, audit, and governance expectations related to AI, model governance, data governance, and enterprise controls.
• Hands-on experience governing AI/ML, LLM, Generative AI, RAG, and advanced analytics solutions within enterprise environments.
• Strong familiarity with enterprise governance tooling including Microsoft Purview, Collibra, Alation, Informatica, MLflow, model registries, monitoring platforms, and AI observability solutions.
• Practical understanding of cloud data and AI ecosystems including Azure, Databricks, Snowflake, AWS, GCP, and modern data platforms.
• Strong understanding of metadata management, data lineage, access governance, data lifecycle management, retention, and enterprise data quality controls.
• Experience partnering across business, technology, risk, compliance, legal, cybersecurity, audit, and operations teams to operationalize governance at scale.
• Strong analytical, executive communication, and stakeholder management skills with the ability to translate complex AI and governance risks into actionable business decisions.
• Bachelor’s degree in Information Systems, Computer Science, Data Management, Risk Management, Business Analytics, or related discipline.

Highly Preferred

• Direct experience governing enterprise AI/GenAI programs within banking or highly regulated industries.
• Strong familiarity with banking regulatory frameworks and governance expectations including SR 11-7, BCBS 239, CCAR, CECL, AML/BSA, privacy, and enterprise risk management standards.
• Experience governing LLM platforms including OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Bedrock, or open-source models.
• Hands-on experience with AI governance related to RAG architectures, vector databases, AI monitoring, prompt governance, and model evaluation frameworks.
• Experience implementing governance controls supporting AI explainability, fairness, auditability, monitoring, and evidence management.
• Strong understanding of AI/ML lifecycle management, MLOps, model registries, and production monitoring frameworks.
• Professional certifications such as CDMP, DAMA, Collibra, Microsoft Purview, risk management, or AI governance certifications.
• Master’s degree or advanced degree in Data Management, AI, Risk Management, Computer Science, or related quantitative discipline.

Applicants must have legal authorization to work in the United States.  We do not offer visa sponsorship at this time.