Data Product & AI Enablement Manager

MUFG•Walnut Creek, CA

3d•$176,000 - $234,000•Hybrid

About The Position

The Data Product & AI Enablement Manager is responsible for defining, building, and managing enterprise data products and AI-enabled capabilities that drive business outcomes, operational efficiency, regulatory compliance, and innovation. This role serves as the bridge between business stakeholders, technology teams, data engineering, analytics, and AI specialists to ensure data and AI investments deliver measurable value. The position will establish product strategy, prioritize roadmaps, oversee delivery, and drive adoption of data and AI solutions across the organization. The incumbent will lead cross-functional teams and collaborate with business leaders to identify opportunities where data products, machine learning, generative AI, and automation can improve decision-making, customer experience, risk management, and productivity.

Requirements

Bachelor's degree in Computer Science, Data Science, Finance, Information Systems, Engineering, Business, or related field.
8–12+ years of experience in product management, data management, analytics, technology, or related disciplines.
3–5+ years leading cross-functional teams or direct reports.
Experience delivering enterprise data products or AI-driven solutions.
Demonstrated success driving business transformation through data and technology.
Strong understanding of: Data products and data governance, Data architecture and cloud platforms, AI/ML and Generative AI technologies, Data visualization and analytics, Agile methodologies and product management practices
Strategic thinking and business acumen.
Ability to influence senior executives and drive decision-making.
Strong communication and stakeholder management skills.
Results-oriented mindset with a focus on delivering measurable business value.
Ability to translate complex technical concepts into business outcomes.

Nice To Haves

Master's degree preferred.
Experience operating within complex, regulated environments preferred.
Familiarity with: Snowflake, Databricks, Azure AI, Microsoft Fabric, Microsoft Copilot, Large Language Models (LLMs), Data marketplaces and APIs

Responsibilities

Develop and execute the vision, strategy, and roadmap for enterprise data products.
Define product objectives, success metrics, and value realization plans.
Partner with business stakeholders to understand requirements and prioritize product enhancements.
Create and manage data product backlogs and delivery roadmaps.
Establish governance, ownership, and lifecycle management for data products.
Identify and evaluate opportunities to leverage AI, machine learning, and generative AI capabilities.
Lead the design and implementation of AI-enabled business solutions.
Partner with technology and risk teams to ensure responsible AI practices are embedded into all solutions.
Drive adoption of AI platforms, copilots, intelligent automation, and agentic AI capabilities.
Monitor AI performance, value realization, and business impact.
Work closely with engineering, architecture, analytics, and business teams to deliver scalable solutions.
Lead Agile product management practices including roadmap planning, backlog prioritization, sprint reviews, and stakeholder engagement.
Manage dependencies across multiple teams and initiatives.
Ensure solutions meet quality, security, data governance, and regulatory requirements.
Serve as the primary liaison between business leaders and delivery teams.
Communicate product strategy, progress, risks, and outcomes to executive stakeholders.
Build strong partnerships across Technology, Operations, Risk, Compliance, Human Resources, Finance, and Business Units.
Promote data quality, lineage, governance, privacy, and security standards.
Ensure compliance with regulatory expectations related to data and AI solutions.
Support model governance, AI controls, and responsible AI frameworks.
Lead, mentor, and develop a team of product managers, analysts, and data professionals.
Foster a culture of innovation, experimentation, and continuous improvement.
Build organizational capabilities in product management, data literacy, and AI adoption.