Senior Director, AI / Machine Learning Software Engineer

BNY Mellon•New York, NY

1d•Onsite

About The Position

Head of AI Garage, Wealth & Investment Management Engineering 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 Head of AI Garage, Wealth & Investment Management Engineering to join our Wealth & Investment Management Engineering team. This role is located in New York City / Jersey City

Requirements

10+ years in data/AI engineering or applied ML, including 5+ years leading teams delivering production AI systems in regulated environments.
Proven delivery of enterprise-scale GenAI solutions (e.g., RAG, conversational assistants, document intelligence) with measurable business outcomes; deep experience with LLMs and orchestration (Gemini, Claude, OpenAI; LangChain/LangGraph, DSPy, LlamaIndex), vector embeddings and retrieval (FAISS, Pinecone, Weaviate, pgvector, OpenSearch), knowledge graphs/semantics (GraphDB/Neo4j/Neptune; RDF/OWL, SHACL), and data engineering (Python/Java/Scala; Spark/Flink; SQL/NoSQL; data quality, lineage, metadata).
Expertise in cloud-native architecture (Kubernetes, microservices, API design, CI/CD, observability, secrets management), privacy/security and controls for financial services (PII handling, encryption, entitlements, model governance), and excellent communication skills to translate complex AI topics into clear business narratives and technical designs.
Demonstrated people leadership: ability to hire, develop, and lead cross-functional teams (applied scientists, data/graph engineers, LLM engineers, evaluators, product leads) while fostering a culture of craftsmanship, security-by-design, and measurable business impact.

Responsibilities

Build and lead the AI Garage to accelerate, de-risk, and scale GenAI solutions across Wealth Services, Investment Management, and Wealth Management; develop a high-velocity pipeline of use cases aligned to business objectives with a transparent roadmap and OKRs.
Establish enterprise-grade data readiness for AI, semantic data foundations, and reusable GenAI platforms, including standards for data quality, lineage, provenance, privacy classifications, and data contracts; implement feature stores, prompt-context catalogs, and instrumentation for usage and drift.
Design and operate semantic data and knowledge graph capabilities and vector retrieval infrastructure; implement high-quality RAG pipelines, re-rankers, and citation grounding with robust embedding governance to improve factuality, explainability, and compliance.
Deliver end-to-end GenAI applications and LLMOps capabilities (experiment tracking, registries, evaluations, safety filters, prompt/version management); integrate securely with enterprise systems, ensuring scalability, observability, disaster recovery, and alignment with governance, risk, and compliance requirements.