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About the Role
This role leads a strategic engineering function supporting enterprise and business priorities through modern data, AI, and platform capabilities. It operates at the intersection of business, data, AI, technology, architecture, risk, governance, and transformation, aiming to strengthen engineering capabilities, drive execution excellence, and improve data accessibility, context management, interoperability, controls, and business value through AI-enabled platforms and knowledge graph capabilities. A core part of this role is shaping and scaling the firm’s AI context layer, including knowledge graph, semantic, and metadata-driven capabilities, and driving AI-led engineering and solutioning to modernize delivery and accelerate development.
Responsibilities
- 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 value.
- Oversee delivery of strategic programs across the function, ensuring strong execution discipline, governance routines, issue remediation, dependency management, performance tracking, and continuous improvement.
- Lead risk, control, and operational oversight across the function, ensuring strong governance, resiliency, regulatory awareness, and disciplined execution in a highly controlled environment.
- Manage budgets, resource allocation, and investment priorities in support of strategic plans and sustainable business performance.
- Recruit, develop, and retain strong talent while fostering an inclusive, accountable, and high-performance culture grounded in collaboration, curiosity, innovation, and continuous improvement.
- Represent the organization in senior leadership forums, translating complex data, AI, engineering, and transformation priorities into clear business value, strategic tradeoffs, and actionable outcomes.
- Build trusted relationships with internal stakeholders and senior leaders, serving as a strategic partner who can navigate complexity, solve problems, and drive alignment across a matrixed organization.
Requirements
- Bachelor’s degree or the equivalent combination of education and experience is required; advanced degree preferred.
- Significant experience in financial services or another highly regulated industry, with strong exposure to data engineering, AI/ML platforms, enterprise architecture, metadata, governance, or digital transformation.
- Extensive experience in a senior leadership role leading large-scale data, AI, engineering, platform, or solution delivery functions in complex enterprise environments.
- Proven ability to lead large, matrixed organizations, including demonstrated success in people leadership, organizational design, and leadership development.
- Strong track record of delivering transformation and modernization initiatives at scale, including platform engineering, process redesign, operating model improvement, automation, and control adoption.
- Demonstrated experience building and scaling enterprise data and AI capabilities, including modern data platforms, contextual data services, metadata-driven solutions, or knowledge-centered architectures.
- Experience with AI context layer concepts, such as knowledge graphs, semantic models, ontologies, metadata frameworks, lineage, graph-based relationships, or contextual retrieval patterns, and how they can be applied to enterprise business and technology use cases.
- Demonstrated experience applying AI-enabled capabilities to improve engineering productivity, solution quality, workflow efficiency, interoperability, decision-making, or business outcomes.
- Deep understanding of operational risk, controls, governance, and regulatory expectations in highly regulated environments.
- Strong business and stakeholder leadership skills, with the ability to influence across business, technology, architecture, risk, compliance, operations, and senior leadership teams.
- Experience managing budgets, workforce planning, and strategic investment prioritization.
- Proven ability to establish and maintain trusted business partnerships across a matrixed organization.
- Strong judgment, problem-solving capability, and execution discipline in a dynamic environment with evolving priorities.
Skills
- Data engineering
- AI/ML platforms
- Enterprise architecture
- Metadata
- Governance
- Digital transformation
- People leadership
- Organizational design
- Leadership development
- Platform engineering
- Process redesign
- Operating model improvement
- Automation
- Control adoption
- Knowledge graphs
- Semantic models
- Ontologies
- Metadata frameworks
- Lineage
- Graph-based relationships
- Contextual retrieval patterns
- AI-enabled capabilities
- Operational risk
- Stakeholder leadership
- Workforce planning
- Strategic investment prioritization
- Business partnerships
- Problem-solving
- Execution discipline
- Data pipelines
- Data platforms
- Semantic services
- Stewardship-aligned engineering models
- Contextual data architecture
- Graph-based data modeling
- Semantic technologies
- Entity relationship frameworks
- AI solution architecture
- Retrieval patterns
- Contextual grounding
- Model integration
- Workflow orchestration
- Responsible AI implementation
- Operating model transformation
- API-enabled architecture
- Cloud-based engineering patterns
- Governance tooling
- AI-enabled developer productivity practices
Location
- New York City, NY
Work Type
- Full-time
Experience Level
- Senior leadership
- Senior Director
Education Level
- Bachelor’s degree or equivalent combination of education and experience
- Advanced degree preferred
Salary/Compensations
- The expected base salary for this position when employment commences can be found in the Job Info section at the bottom of the posting.
- Base salary offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.
- Base salary is only part of the total rewards package, which may include eligibility for an annual discretionary incentive award.
Benefits
- Highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and pay-for-performance philosophy.
- Access to flexible global resources and tools.
- Focus on health, personal resilience, and financial goals.
- Generous paid leaves, including paid volunteer time.
- 401(k) plan
- Company-sponsored medical, dental, vision, and basic life insurance plans.
- Various paid time off benefits, such as vacation and sick time.
About the Company
- BNY is a leading global financial services company at the heart of the global financial system, influencing nearly 20% of the world’s investible assets.
- Teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.
- BNY is recognized as a top destination for innovators where bold ideas meet advanced technology and exceptional talent.
- BNY Newsroom: https://www.bny.com/corporate/global/en/about-us/newsroom.html
- BNY LinkedIn: https://www.linkedin.com/company/bnyglobal/posts/?feedView=all
- Awards: America’s Most Innovative Companies, Fortune, 2025; World’s Most Admired Companies, Fortune 2025; “Most Just Companies”, Just Capital and CNBC, 2025.
Equal Opportunity
- BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.