Applied AI Technical Product Manager

Job Description Director, Technical Product Manager: 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 is all about. Join us and be part of something extraordinary.

We’re seeking a future team member for the role of Director, Technical Product Manager to join our Innovation Team and lead AI-driven business transformation initiatives that reimagine how work gets done across the bank. This leader will combine deep technical fluency in AI systems with strong product strategy and execution experience in large, complex organizations. The ideal candidate has successfully built and scaled AI-enabled platforms, led multidisciplinary teams, and driven measurable business outcomes in regulated enterprise environments.

This role is located in New York, NY (4 days in office per week).

Role Overview As Director, Technical Product Manager, you will define and drive the strategy for AI-powered process transformation across enterprise functions. You will lead cross-functional teams to design, build, and scale agentic and intelligent automation solutions that reduce risk, improve operational efficiency, and enhance client experiences. You will operate at the intersection of Product, Engineering, Data Science, Operations, Risk, and Compliance—ensuring solutions are secure, explainable, scalable, and production-ready.

In this role, you’ll make an impact in the following ways: Product Vision & Strategy

• Define and own the product vision, strategy, and roadmap for AI-driven business process transformation initiatives with key business stakeholders
• Align roadmap priorities to enterprise modernization, AI strategy, and operational efficiency objectives
• Identify high-value opportunities for AI, intelligent automation, LLMs, and agentic architectures to eliminate manual workflows and enhance decision intelligence (transform business processes into digital products)
• Translate ambiguous, complex business problems into clear product tenets, PR/FAQs, and scalable execution plans
• Champion an AI-first mindset across the organization, embedding modern product thinking and experimentation frameworks

AI-Native Process Reimagination at Scale

• Oversee orchestration frameworks spanning:

• Event-driven architecture
• APIs and microservices
• Workflow engines and state management
• Metadata-aware retrieval systems

• Multi-agent coordination models

• Balance innovation velocity with enterprise-grade reliability and governance
• Partner with Engineering and Data Science to operationalize AI at scale, incorporating model lifecycle management, observability, guardrails, and performance optimization
• Ensure responsible AI governance, addressing bias, explainability, privacy, data security, and operational resilience

Execution & Cross-Functional Delivery

• Influence senior executives on investment prioritization and enterprise adoption
• Translate complex AI and agentic concepts into clear, outcome-driven business narratives
• Drive adoption through executive storytelling and structured change management
• Lead a high-performing product team with strong systems-thinking capabilities
• Remove blockers, align stakeholders, and ensure consistent value delivery across concurrent workstreams

Enterprise & Stakeholder Leadership

• Partner with senior executives and enterprise stakeholders to align AI strategies with business objectives
• Communicate vision, strategy, progress, and measurable impact to leadership
• Drive field-to-product feedback mechanisms to continuously refine AI solutions for enterprise-grade performance
• Enable adoption through playbooks, governance frameworks, and change management strategies

Impact Measurement & Outcomes

• Define and track clear success metrics including:

• Productivity gains and operational efficiency improvements (e.g., 20-50% time reduction)
• Cost savings and automatio…