Senior Vice President, Applied AI Product Manager

BNY MellonNew York, NY
Hybrid

About The Position

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 Senior Vice President, Applied AI Product Manager to join our Innovation Team and drive the design, development, and delivery of AI-powered solutions that transform how work gets done across the bank. This leader will partner closely with product, engineering, and business teams to operationalize AI capabilities and bring intelligent automation platforms to production at enterprise scale. This role is located in New York, NY (4 days in office per week). Role Overview: As Senior Vice President, Applied AI Product Manager, you will lead the development and execution of AI-driven products that modernize business processes and enable scalable automation across enterprise functions. You will partner with engineering, data science, and business stakeholders to translate complex operational challenges into AI-enabled solutions that improve efficiency, reduce risk, and enhance client outcomes. You will focus on product execution, platform delivery, and adoption, ensuring solutions are reliable, scalable, and aligned with enterprise governance standards.

Requirements

  • 8–10 years of experience in Applied AI product management, AI-enabled product development, or enterprise software delivery
  • Strong understanding of: AI-powered product capabilities, Generative AI, Intelligent automation and agentification
  • Experience working with engineering and data science teams to deliver applied AI products
  • Knowledge of enterprise architecture patterns including APIs, microservices, and distributed systems
  • Ability to translate complex business challenges into scalable technical solutions
  • Strong product delivery, prioritization, and stakeholder management skills
  • Bachelor's degree in STEM or related discipline

Nice To Haves

  • Experience implementing LLM-based solutions or intelligent automation platforms
  • Familiarity with AI lifecycle management, model monitoring, and observability tools
  • Experience working in regulated or enterprise environments
  • Certifications: CSPO, A-CSPO, SAFe POPM, CSM, AWS Cloud Practitioner, Generative AI specialization.
  • Advanced degree preferred

Responsibilities

  • Execute the applied AI product roadmap aligned to enterprise AI strategy and platform priorities
  • Translate business needs into product requirements, backlog priorities, and release plans
  • Identify opportunities for AI-enabled automation within specific domains or workflows
  • Work with engineering and data science to refine technical solutions and product features
  • Translate operational challenges into AI-enabled features, automation workflows, or decision-support tools
  • Support development of LLM-powered solutions, intelligent automation, and agent-enabled workflows
  • Work with platform teams to implement AI capabilities within existing business processes
  • Leads delivery of specific AI products or capabilities across product, engineering, and data science teams
  • Coordinates development, testing, and deployment of AI-enabled solutions
  • Removes blockers and ensures alignment within product delivery teams
  • Work with engineering, data science, and operational stakeholders to deliver AI product features
  • Communicate requirements, priorities, and delivery progress
  • Help translate technical capabilities into practical business outcomes
  • Track product-level metrics such as automation adoption, workflow efficiency, and user engagement
  • Use feedback and data to iterate and improve AI product performance

Benefits

  • generous paid leaves
  • paid volunteer time
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