Enterprise AI Strategy & Transformation at East West Altadena, California

AI Strategy Lead

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.

Lead execution of East West Bank's AI strategy by converting priority use cases, pilots, and proofs of concept into governed, measurable, and scalable adoption. This role will establish the operating discipline required to move AI from experimentation to enterprise implementation, with clear ownership, delivery standards, risk controls, adoption metrics, and executive visibility.

The role will work across business, technology, data, risk, compliance, and vendors to ensure AI initiatives are prioritized against business value, delivered through a repeatable model, responsibly scaled, and measured for impact.

Responsibilities:

• Develop reusable UX patterns, workflow standards, prompt guidance, and adoption playbooks for AI-enabled tools and processes.
• Create common design principles for employee-facing and customer-facing AI experiences to improve consistency, usability, trust, and adoption.
• Partner with product, design, technology, and business teams to identify repeatable AI workflows that can scale across multiple functions.
• Establish a repeatable delivery model for moving AI initiatives from idea to POC, pilot, launch, and enterprise scale.
• Define stage gates, entry and exit criteria, success metrics, risk checkpoints, ownership requirements, and production-readiness standards.
• Ensure POCs have clear success measures before launch, including usage, productivity, quality, cost, risk, and employee or customer impact.
• Coordinate readiness across technology, data, model governance, controls, support, training, and business ownership.
• Track whether AI initiatives are delivering measurable value after launch and create an evidence base for scaling, redesigning, pausing, or retiring initiatives.
• Define standard metrics and leadership reporting routines for AI adoption, usage, productivity, quality, cost, risk, and business value.
• Create executive-ready dashboards, summaries, and narratives that connect AI portfolio activity to enterprise outcomes, funding decisions, and leadership priorities.
• Translate AI strategy into a prioritized execution roadmap across business, technology, data, risk, compliance, and governance.
• Maintain visibility across AI products, pilots, POCs, vendor efforts, and business-led experiments to reduce duplication and improve portfolio discipline.
• Build a standard intake and scoring model to evaluate AI use cases based on business value, feasibility, data readiness, risk, compliance impact, adoption potential, cost, and scalability.
• Serve as a cross-functional execution lead across business, technology, data, risk, compliance, legal, procurement, and vendor teams.
• Clarify decision rights, ownership, dependencies, escalation paths, and accountability for AI initiatives, vendor pilots, deliverables, timelines, and measurable outcomes.

Key Outcomes:

• Reusable AI UX, workflow, prompt, and adoption standards that improve consistency and scalability.
• A repeatable POC-to-production framework with stage gates, success metrics, controls, and readiness checks.
• A standard AI use case intake and scoring model tied to measurable business value.
• Standardized reporting on AI adoption, value, cost, quality, risk, and portfolio progress.
• A prioritized AI roadmap with clear ownership, timelines, dependencies, and executive decision points.
• Stronger coordination across business, technology, data, risk, compliance, and vendors.
• Faster leadership decisions on which AI initiatives to test, build, scale, pause, retire, or fund.

Required:

• 12+ years of experience in AI/ML, digital transformation, or enterprise technology strategy roles, including 5+ years in executive leadership.
• Proven ability to scale AI initiatives across a global, matrixed organization.
• Deep familiarity with AI/ML technologies (e.g. LLMs, computer vision, predictive analytics), data science workflows, and cloud platforms (Azure, AWS, GCP).
• Demonstrated experience in organizational change management and capability building.

Preferred:

• Advanced degree in Computer Science, Data Science, Business Administration, or a related field.
• Experience leading governance programs for AI, data privacy, or emerging technologies. Strong understanding of business architecture and value stream mapping.
• Public speaking experience and a strong executive presence.

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

Compensation: The base pay range for this position is USD $150,000.00/Yr. - USD $250,000.00/Yr. Exact offers will be determined based on job-related knowledge, skills, experience, and location.