AI-Forward Product Manager — Director, AI Transformation Office at BNY Mellon

AI-Forward Product Manager — Director, AI Transformation Office

We are looking for a hands-on, AI-forward Product Manager to drive day-to-day product execution within BNY's centralized AI Transformation Office, serving Markets and Execution lines of business.

This is not a BAU product manager hire. Where a traditional PM manages timelines and stakeholder updates, an AI-forward Product Manager actively shapes how AI capabilities are applied - understanding model behavior, evaluating agentic workflow design, and identifying where LLMs create genuine product value versus where they introduce risk. This role sits at the intersection of business, data, and AI engineering - and requires someone who can operate fluently across all three.

• Own end-to-end product delivery for assigned AI initiatives - from use case definition through to deployment and iteration
• Work hands-on with LOB stakeholders and engineering to define requirements, validate AI outputs, and ensure solutions are fit for purpose
• Contribute to backlog prioritization and sprint planning alongside Product Owners and engineering leads
• Evaluate and document AI model behavior, edge cases, and failure modes as part of the product definition process
• Support consistent governance and delivery standards across the AI Transformation Office
• Vast product management experience, with direct, hands-on involvement in AI or GenAI product delivery

Required Skills

• Working knowledge of LLMs, prompt engineering, and agentic workflow design - enough to have an informed technical conversation with engineers
• Experience translating complex business requirements into structured AI product specs
• Proficiency with AI-native productivity tools across research, documentation, and workflow management
• Strong communication and stakeholder engagement skills across business and technology teams

Preferred

• Experience with workflow automation platforms or agentic frameworks
• Familiarity with RAG pipelines, vector databases, or LLM evaluation approaches
• Financial services background
• Markets, Execution, or related domains
• Agile delivery experience in a fast-paced, innovation-focused environment