Director, Technical Product Manager
Listed on 2026-03-05
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IT/Tech
Data Science Manager, AI Engineer
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.
This role is located in New York, NY (4 days in office per week).
Role OverviewAs 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
- 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
- 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 work streams
- 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
- Define and track clear success metrics including:
- Productivity gains and operational efficiency improvements (e.g., 20-50% time reduction)
- Cost savings and automation impact
- Risk mitigation and compliance enhancements
- Client experience and engagement growth
- Demonstrate measurable business impact through scalable AI platforms and intelligent workflow transformation
Required
- Bachelor's degree in STEM, Economics, or related discipline
- ~Ten years of progressive experience in technical product management, program leadership, or AI-driven platform delivery
- Strong understanding of:
- Generative AI and LLM-powered systems
- Agentic architectures and orchestration frameworks
- Distributed systems and microservices
- Event-driven design
- APIs and integration layers
- Metadata…
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