Director, Product Owner – Applied AI Data Integration

Application Deadline:

02/27/2026

Address:

320 S Canal Street

Job Family Group:

Data Analytics & Reporting

Please note this role is Hybrid (3 days per week in office) subject to company policy changes.

We accelerate BMO’s AI journey by building enterprise-grade, cloud-native AI solutions. Our team combines engineering excellence with cutting-edge AI to deliver scalable, secure, and responsible solutions that power business innovation across the bank. We enable and accelerate our partners on their AI journeys across the enterprise, helping teams across BMO unlock value at scale. We are engineers, AI practitioners, platform builders, thought leaders, multipliers, and coders. Above all, we are a global team of diverse individuals who enjoy working together to create smart, secure, and scalable solutions that make an impact across the enterprise. Our ambition is bold: deploy our capital and resources to their highest and most profitable use through a digital-first operating model, powered by data and AI-driven decisions.

About the Role

As Director, Product Owner – Applied AI Data Integration, you will play a senior leadership role within BMO’s ARC/Applied AI organization, accountable for shaping and delivering data integration and platform capabilities, accelerating scalable and responsible AI solutions that enable strategic value creation. This role blends hands-on Product Ownership with strategic leadership, ensuring data is accessible, governed, and fit-for-purpose to unlock measurable business value.

You will lead one or more cross-functional pods of engineers, data engineers, and data scientists while partnering closely with other ARC/Applied AI Product Owners and delivery stakeholders. You will be a key driver product market fit, adoption, and commercialization, operating in a highly regulated financial services environment.

Key Responsibilities

Product Ownership & Delivery (Primary Accountability)

• Own the end-to-end product lifecycle for Applied AI data integration capabilities, from strategy and roadmap through delivery, scaling, and optimization.
• Lead cross-functional teams to design, build, and operate data pipelines, feature stores, and integration services that support AI/ML and GenAI use cases.
• Ensure data is “fit for purpose”, enabling superior results as measured by contextual evaluation standards and thresholds.
• Translate business and analytic needs into clear product requirements, epics, and prioritized backlogs.
• Ensure platforms are designed for scalability, reliability, security, and reuse across the ARC/Applied AI product, feature, and service portfolio.
• Embed Agile and modern product management practices to enable rapid iteration and continuous improvement.

Responsible AI, Data Governance & Risk

• Champion responsible AI and data practices, ensuring compliance with BMO’s data governance, privacy, security, and ethical AI standards.
• Partner with Risk, Compliance, Legal, and Data Governance teams to ensure data integration solutions meet regulatory and audit expectations.
• Design products with explainability, lineage, quality, and controls by default.

Strategy, Roadmap & Value Realization

• Define and continuously evolve a clear product vision and multi-year roadmap for Applied AI data integration capabilities.
• Identify, validate, and scale high-impact use cases aligned with BMO’s strategic priorities.
• Establish success metrics and OKRs tied to outcomes spanning customer, financial, data, risk, and a winning culture.
• Communicate progress and outcomes to senior executives, translating technical capabilities into business value narratives.

People & Leadership

• Recruit, lead, and develop high-performing, multidisciplinary teams across data engineering, platform engineering, and data product management.
• Foster a culture of collaboration, inclusion, accountability, and continuous learning aligned with BMO’s Winning Culture.
• Provide coaching, mentorship, and succession planning to ensure sustainable team performance and growth.

Partner & Vendor Management

• Collaborate with internal technology teams and external vendors to deliver platform capabilities while effectively managing supplier risk.
• Ensure appropriate governance, financial stewardship, and performance management of third-party solutions.

Key Success Measures

• Scalable, reliable data integration platforms enabling AI/GenAI delivery at enterprise scale.
• Measurable acceleration of AI product delivery and business value realization.