Vice President, AI/ML Software Engineer

**JOB DESCRIPTION** 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 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) …