Vice President, AI

Vice President AI/ML Software Engineer

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 and champions of inclusion, 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 are seeking a Vice President AI/ML Software Engineer to design and implement agentic AI systems, RAG pipelines, and intelligent document processing services. This is a senior individual contributor role with high autonomy -- you will own significant components of our AI platform, from embedding pipelines and vector retrieval to multi-agent extraction workflows. You will work closely with the SVP lead to translate architectural vision into production code, while mentoring mid-level engineers and driving technical excellence across the team. This role is in New York, NY

What Sets This Role Apart

• You build the agent framework, not just configure one -- custom orchestration engine, not a LangChain wrapper
• Production AI with real consequences -- extraction accuracy directly impacts financial operations
• Full RAG ownership -- from raw OCR bytes through embedding, retrieval, and generation
• Evaluation-driven culture -- golden-truth datasets, automated regression, measurable quality gates
• Greenfield AI + enterprise integration -- build new AI-native systems that plug into established platforms

In this role, you'll have the opportunity to impact on our organization in the following ways:

AI Systems Development

• Implement agentic pipelines: agent loops, tool registries, memory stores, reasoning traces, and self-correction mechanisms
• Build and optimize RAG systems end-to-end:
• Document ingestion and preprocessing (OCR output, PDFs, structured/unstructured text)
• Chunking strategies (section-aware, semantic, sliding window, hierarchical)
• Embedding generation and vector index management
• Retrieval orchestration: hybrid search, metadata filtering, re-ranking
• Context assembly and prompt construction for downstream LLM calls
• Develop vectorization pipelines -- embedding model integration, batch processing, incremental index updates, and similarity search tuning
• Implement multi-agent coordination patterns: shared blackboards, inter-agent messaging, task decomposition, and consensus mechanisms
• Build prompt engineering infrastructure: template management, few-shot example selection, chain-of-thought scaffolding, and output parsing
• Develop evaluation harnesses: automated accuracy measurement, retrieval quality metrics, regression detection, and A/B comparison tooling

Platform & Backend Engineering

• Build FastAPI services exposing AI capabilities as production APIs (extraction, validation, classification)
• Contribute to Java/Spring Boot platform services where AI integrates with business workflow
• Design and maintain database schemas for AI metadata: audit trails, pipeline runs, memory entries, knowledge graphs
• Implement content policy enforcement and data governance controls within AI pipelines

Mentorship & Collaboration

• Mentor 2-3 mid-level engineers on AI engineering practices
• Participate in architecture reviews and design sessions
• Document patterns, decisions, and runbooks for AI system operation
• Collaborate with product and business stakeholders to translate requirements into technical solutions

To be successful in this role, we're seeking the following:

• Bachelor's degree in Computer Science, Engineering, or related field.
• Advanced degree preferred.
• 6+ years of professional software engineering experience
• 2+ years building production AI/ML systems (not just notebooks/prototypes. Strong problem-solving skills with the ability to manage complex data processes. )
• Excellent collaboration and communication skills to work effectively with cross-functional teams. )

Strong RAG expertise:

• Embedding models (OpenAI, sentence-transformers, Cohere, or similar)
• Vector databases (FAISS, Pinecone, Weaviate, Chroma, pgvector, or similar)
• Chunking and retrieval optimization
• Context window management and prompt assembly

Agentic