Vice President, POM Product Owner

BNY Mellon•Pittsburgh, PA

20h•Onsite

About The Position

Vice President, Product Owner At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. We’re seeking a future team member for the role of Vice President, Product Owner to join the Conventional Trust Deal Administration group, supporting our deal onboarding and end-to-end deal lifecycle management process and applications. This role is located in Pittsburgh, PA or Lake Mary, FL. In this role, you’ll make an impact in the following ways: Own the product vision and roadmap, leveraging agentic AI to transform manual workflows into straight ‑ through processing (STP) and exceptions ‑ based management. Define user stories end-to-end, including refinement and ongoing backlog grooming. Define, own and prioritize the product backlog, translating future-state operational workflows into clear requirements and acceptance criteria Define and own the functional capabilities and UI required to support end‑to‑end exception management, including decisioning logic, escalation criteria, and human‑in‑the‑loop intervention points. Conduct structured discovery sessions with operations SMEs to document current-state processes, decision logic, data inputs/outputs, system touchpoints and exception triggers. Serve as the primary liaison between engineering teams and operations, translating operational friction points into scalable automation solutions. Define data requirements for automation and partner closely with data analysts and engineers to identify and source the data needed to enable accurate and reliable task execution.

Requirements

8 years of experience in product management, data delivery, or technology leadership within financial services
Familiarity with workflow orchestration platforms (e.g. Camunda) and agentic AI frameworks
Product leader with a demonstrable history of delivering value to business and clients in agile environments
Ability to work in fast-paced, client-driven environments with high expectations for data accuracy and performance.
Exceptional leadership and stakeholder management skills, with the ability to influence across technical and business teams.
Possesses a “get-it-done” attitude – ability to get around roadblocks and stay focused on the vision.
Client focus and empathy – ability to bring everyone together, help them grow and work towards a unified vision, and deliver high-quality products that delight customers and align to their vision.

Responsibilities

Own the product vision and roadmap, leveraging agentic AI to transform manual workflows into straight-through processing (STP) and exceptions-based management.
Define user stories end-to-end, including refinement and ongoing backlog grooming.
Define, own and prioritize the product backlog, translating future-state operational workflows into clear requirements and acceptance criteria.
Define and own the functional capabilities and UI required to support end-to-end exception management, including decisioning logic, escalation criteria, and human-in-the-loop intervention points.
Conduct structured discovery sessions with operations SMEs to document current-state processes, decision logic, data inputs/outputs, system touchpoints and exception triggers.
Serve as the primary liaison between engineering teams and operations, translating operational friction points into scalable automation solutions.
Define data requirements for automation and partner closely with data analysts and engineers to identify and source the data needed to enable accurate and reliable task execution.