Associate Vice President - Workflow Automation

The Associate Vice President, AI Product Manager leads the AI Lab's Internal Productivity squad. The role is accountable for delivering AI products that make the bank more knowledgeable, more efficient, and measurably more productive, with a primary focus on the bank's enterprise knowledge engine, its knowledge management capabilities, and the AI tools and platforms used across the organization. The role combines hands-on product leadership with squad management. It is responsible for translating strategic priorities into a clear roadmap, leading a multi-disciplinary squad through delivery, and partnering with departments across the bank to help them capitalize on AI tooling and realize meaningful productivity gains and cost reduction. What You Will Do: Product Leadership and Roadmap Define and own the product strategy and roadmap for the Internal Productivity squad, anchored around the enterprise knowledge engine and the bank's knowledge management capabilities. Translate business problems and user pain points into clear product opportunities, user stories, and measurable success criteria. Maintain a prioritized backlog that balances customer value, technical health, and strategic ambitions. Knowledge Management and Enterprise Knowledge Engine Lead product development of the bank's knowledge management system and enterprise knowledge engine, including retrieval, search, and intelligent assistance experiences. Identify and shape adjacent opportunities such as next-best-action models, recommendation engines, and decision-support assistants powered by enterprise knowledge. Partner with knowledge owners, business SMEs, and content teams to ensure the engine is fed with high-quality, well-governed information. AI Enablement, Tools, and Democratization Lead AI enablement initiatives across departments, helping teams adopt and capitalize on the AI tools and platforms rolled out by the AI Lab. Build playbooks, templates, and onboarding journeys that accelerate adoption and demonstrate measurable productivity gains and cost reduction. Drive the democratization agenda for AI inside the bank, expanding the population of confident, capable AI users across functions. Squad Leadership and Delivery Lead the squad through agile ceremonies including planning, refinement, stand-ups, reviews, and retrospectives. Take accountability for on-time delivery, release quality, and overall team health. Coach and develop squad members, set clear expectations, and remove blockers in partnership with the AI Delivery Lead and the Head of AI Lab. Stakeholder Management. Build trusted relationships with department heads, function leads, and AI Champions across the bank. Run regular product reviews, demos, and adoption forums to communicate progress, capture feedback, and steer roadmap decisions. Translate technical progress into clear business outcomes for senior stakeholders. Cross-Functional Alignment Work closely with peer squads inside the AI Lab to share platform components, reusable assets, and design patterns. Align with Enterprise Architecture, Technology Delivery, Information Security, Risk, and Compliance to ensure responsible delivery. Operate as an active member of the bank's Agile community and contribute to the maturity of its product practice. Decision-Making Authority Backlog prioritization and release scope for the Internal Productivity squad. Product design and user experience decisions within the agreed strategy and budget. Recommendations on AI tools, platforms, and partners for internal productivity use cases. Squad composition and resourcing recommendations in collaboration with the Head of AI Lab and the AI Delivery Lead. What We Are Looking For: Bachelor's degree in Computer Science, Engineering, Information Systems, Business, or a related discipline. A post-graduate qualification is welcome but not required. 6 -7 years of professional experience, with at least 3 years in product management, product ownership, or AI and data product delivery roles. Hands-on experience delivering technology or AI products end-to-end inside an agile environment. Working knowledge of generative AI, large language models, and retrieval-augmented generation (RAG) patterns is preferred. Exposure to knowledge management, enterprise search, intranet portals, or workplace productivity tooling is a plus. Experience leading or coordinating multi-disciplinary teams, formally or informally, is preferred. Banking or regulated industry experience is a plus but not mandatory; strong candidates from technology, consulting, or product-led companies will also be considered. Technical Competencies and Proficiency Levels AI and Data Product Management: Expert Generative AI, Large Language Models, and RAG patterns: Advanced Agile Product Delivery and Backlog Management: Expert Knowledge Management and Enterprise Search: Advanced AI Tooling, Platforms, and Adoption Frameworks: Advanced Solution Desig

Bachelor's degree in Computer Science, Engineering, Information Systems, Business, or a related discipline. A post-graduate qualification is welcome but not required. 6-7 years of professional experience, with at least 3 years in product management, product ownership, or AI and data product delivery roles. Hands-on experience delivering technology or AI products end-to-end inside an agile environment. Working knowledge of generative AI, large language models, and retrieval-augmented generation (RAG) patterns is preferred. Exposure to knowledge management, enterprise search, intranet portals, or workplace productivity tooling is a plus. Experience leading or coordinating multi-disciplinary teams, formally or informally, is preferred. Banking or regulated industry experience is a plus but not mandatory; strong candidates from technology, consulting, or product-led companies will also be considered.

Define and own the product strategy and roadmap for the Internal Productivity squad, anchored around the enterprise knowledge engine and the bank's knowledge management capabilities. Translate business problems and user pain points into clear product opportunities, user stories, and measurable success criteria. Maintain a prioritized backlog that balances customer value, technical health, and strategic ambitions. Lead product development of the bank's knowledge management system and enterprise knowledge engine, including retrieval, search, and intelligent assistance experiences. Identify and shape adjacent opportunities such as next-best-action models, recommendation engines, and decision-support assistants powered by enterprise knowledge. Partner with knowledge owners, business SMEs, and content teams to ensure the engine is fed with high-quality, well-governed information. Lead AI enablement initiatives across departments, helping teams adopt and capitalize on the AI tools and platforms rolled out by the AI Lab. Build playbooks, templates, and onboarding journeys that accelerate adoption and demonstrate measurable productivity gains and cost reduction. Drive the democratization agenda for AI inside the bank, expanding the population of confident, capable AI users across functions. Lead the squad through agile ceremonies including planning, refinement, stand-ups, reviews, and retrospectives. Take accountability for on-time delivery, release quality, and overall team health. Coach and develop squad members, set clear expectations, and remove blockers in partnership with the AI Delivery Lead and the Head of AI Lab. Build trusted relationships with department heads, function leads, and AI Champions across the bank. Run regular product reviews, demos, and adoption forums to communicate progress, capture feedback, and steer roadmap decisions. Translate technical progress into clear business outcomes for senior stakeholders. Work closely with peer squads inside the AI Lab to share platform components, reusable assets, and design patterns. Align with Enterprise Architecture, Technology Delivery, Information Security, Risk, and Compliance to ensure responsible delivery. Operate as an active member of the bank's Agile community and contribute to the maturity of its product practice. Backlog prioritization and release scope for the Internal Productivity squad. Product design and user experience decisions within the agreed strategy and budget. Recommendations on AI tools, platforms, and partners for internal productivity use cases. Squad composition and resourcing recommendations in collaboration with the Head of AI Lab and the AI Delivery Lead.