Senior Director, Data Management Manager

We’re seeking a future team member for the role of Senior Director, Data/AI Engineering Manager to join our team. This role is located in New York and will lead a strategic engineering function supporting enterprise and business priorities through modern data, AI, and platform capabilities. This leader will operate at the intersection of business, data, AI, technology, architecture, risk, governance, and transformation . They will be expected to strengthen engineering and solutioning capabilities, drive execution excellence, and identify opportunities to improve data accessibility, context management, interoperability, controls, and business value through AI-enabled platforms, knowledge graph capabilities, intelligent automation, and AI-led engineering practices . A core part of this role will be shaping and scaling the firm’s AI context layer , including knowledge graph, semantic, and metadata-driven capabilities that improve how data, systems, processes, and business concepts are connected, understood, governed, and used across the organization. This leader will also drive AI-led engineering and solutioning , enabling teams to modernize delivery, accelerate development, improve design quality, and unlock new business capabilities through practical application of AI. This is an opportunity to lead a strategically important function at BNY, helping shape the future of data and AI engineering while building high-performing teams and delivering measurable impact at scale. This role is located in New York City, NY. In this role, you’ll make an impact in the following ways: • Lead a critical Data/AI Engineering function, setting direction for engineering strategy, solution delivery, platform enablement, data interoperability, AI adoption, and organizational performance. • Define and execute the strategic vision for the function, aligning data and AI engineering priorities with business goals, architectural direction, regulatory expectations, risk requirements, and long-term transformation objectives. • Build and lead high-performing teams across a large-scale organization, ensuring strong organizational design, leadership capability, workforce planning, and alignment to enterprise priorities. • Drive the design and implementation of scalable, resilient, and well-controlled data and AI engineering platforms that improve data usability, discoverability, accessibility, and trust across critical business domains. • Lead development of the AI context layer , including knowledge graph, ontology, semantic modeling, metadata, lineage, and contextual data frameworks that connect enterprise data, business concepts, and workflows to improve intelligence, reuse, and decision support. • Establish engineering patterns and architectural standards for integrating structured and unstructured data, metadata, semantic relationships, and contextual services into enterprise AI and data solutions. • Partner across Business, Technology, Operations, Risk, Compliance, Architecture, and other stakeholder groups to align investments, priorities, and execution plans with strategic data and AI objectives. • Advance AI-led engineering and solutioning by identifying and scaling practical use cases for AI across software development, architecture, workflow orchestration, intelligent automation, solution design, and platform productivity. • Drive modernization of engineering practices through automation, reusable frameworks, platform thinking, and AI-assisted delivery approaches that improve speed, quality, resiliency, and operating leverage. • Lead the design and evolution of data and AI governance-aligned engineering capabilities , ensuring strong controls around context management, data usage, explainability, traceability, security, and operational oversight. • Translate emerging AI and data engineering opportunities into executable roadmaps, target-state architectures, and prioritized investments that deliver measurable business