About this opportunity
BNY lists this Senior Vice President, AI / Machine Learning Software Engineer opportunity in new york city, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
JOB DESCRIPTION
Senior 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.
What Sets This Role Apart
You build the agent framework, not just configure one -- custom orchestration engine, not a LangChain wrapper
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:
Technical Leadership & Architecture
Architect agentic AI systems: multi-agent orchestration, tool-use patterns, planning/reasoning loops, and autonomous decision chains
Design and evolve RAG infrastructure: chunking strategies, embedding pipelines, vector store selection, retrieval ranking, and context window optimization
Define vectorization strategy: embedding model selection, dimensionality trade-offs, hybrid search (dense + sparse), and re-ranking approaches
Own the AI pipeline orchestration framework -- blocks, inlets/outlets, blackboards, memory stores, and content policy enforcement
Make build-vs-buy decisions across the AI toolchain (vector databases, agent frameworks, evaluation harnesses, model gateways)
Establish patterns for prompt engineering at scale: prompt versioning, chain-of-thought decomposition, few-shot management, and guardrails
Agentic & RAG Systems
Design multi-agent architectures with shared memory, blackboard patterns, and inter-agent communication protocols
Build autonomous extraction agents capable of planning, tool selection, self-correction, and validation
Implement knowledge graph construction from unstructured documents -- entity extraction, relationship mapping, and graph-based retrieval
Develop evaluation frameworks: retrieval precision/recall, extraction accuracy, agent task completion rates, and hallucination detection
Design feedback loops: human-in-the-loop correction, reinforcement from golden-truth datasets, and continuous prompt refinement
Team Leadership
Lead, mentor, and grow a team of 4-8 engineers (AI/ML, backend, full-stack)
Directly manage a VP-level AI engineer; provide technical guidance and career development
Drive architecture reviews, design sessions, and technical decision-making
Own sprint planning, technical backlog, and delivery commitments
Foster a culture of rapid experimentation balanced with production rigor
Hands-On Engineering
Implement core agentic components: agent loops, tool registries, memory persistence, and reasoning traces
Build embedding pipelines: document preprocessing, chunk boundary detection, metadata enrichment, and vector index management
Develop scoring and validation systems (Bayesian confidence, cross-agent consensus, golden-truth comparison)
Contribute to platform services (Java/Spring Boot) and AI service layer (Python/FastAPI)
Build AI-assisted developer tooling: code generation workflows, automated test generation, and intelligent code review
Delivery & Operations
Own CI/CD pipelines, containerized deployments, and environment promotion
Define observability: agent execution traces, token usage tracking, retrieval quality metrics, and pipeline telemetry
Manage schema evolution and data stores (relational + vector)
Coordinate cross-team dependencies with platform engineering, data engineering, and infrastructure
To be successful in this role, we’re seeking the following:
Bachelor's degree or Advanced degree in computer science engineering or a related discipline, or equivalent work experience required.
10+ years of professional software engineering experience.
3+ years leading or technically mentoring engineering teams.
Deep expertise in AI/ML systems: LLM orchestration, prompt engineering, chain-of-thought reasoning.
RAG architectures: chunking, embedding, retrieval, re-ranking, context assembly.
Agentic patterns: ReAct, tool-use, planning loops, multi-agent coordination.
Vector databases and embedding models (OpenAI embeddings, sentence-transformers, FAISS, Pinecone, Weaviate, or similar).
Strong Python (3.11+): FastAPI, async/await, Poetry, Pydantic, pytest.
Solid Java experience: Java 21, Spring Boot 3.x, microservice architecture.
Production AI delivery: not just prototypes -- systems handling real workloads with observability, error recovery, and audit trails.
Document intelligence: OCR pipelines, NLP, structured extraction from unstructured text.
Testing & evaluation: golden-truth validation, retrieval metrics (MRR, NDCG), extraction F1 scores, agent success rates.
Enterprise architecture: API design, circuit breakers, caching, event-driven patterns.
Preferred Qualifications
Experience building custom agent frameworks (not just using LangChain/CrewAI out-of-the-box).
Knowledge of graph-based retrieval -- knowledge graphs, graph RAG, entity-relationship extraction.
Experience with code AI: AI-assisted development tools, code generation pipelines, automated refactoring.
Familiarity with model fine-tuning, LoRA/QLoRA, or RLHF techniques.
Exposure to evaluation-driven development -- automated prompt regression testing, A/B testing of retrieval strategies.
Angular/TypeScript experience for full-stack visibility.
Capital markets or financial services domain knowledge.
Familiarity with enterprise AI governance: content policies, PII handling, data residency.
Technology Stack
AI/Agentic- LLM orchestration, multi-agent systems, ReAct patterns, tool-use, autonomous pipelines
RAG & Vectors- Embedding models, vector stores, hybrid search, re-ranking, chunk optimization
LLM- Azure OpenAI, GPT-4o, enterprise model gateways, prompt versioning
Python- Python 3.12/3.13, FastAPI, Poetry, Pydantic, async pipelines
Java- Java 21, Spring Boot 3.x, Maven, Resilience4j, Hazelcast
Frontend- Angular 19, TypeScript, D3.js, ECharts
Database- Oracle, PostgreSQL, vector databases
Infrastructure- Docker, GitLab CI/CD, Artifactory
Observability- Agent traces, token tracking, retrieval quality metrics, audit pipelines
Our Benefits And Rewards
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.
Equal Employment Opportunity/Affirmative Action Employer
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
At-will Notice
This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.
Compensation Information
BNY assesses market data to ensure a competitive compensation package for our employees. 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. Subject to the terms and conditions of the applicable plans then in effect, eligible employees may enroll in a 401(k) plan as well as participate in Company-sponsored medical, dental, vision, and basic life insurance plans for the employee and the employee’s eligible dependents. Eligible employees also may receive other benefits (including various paid time off benefits, such as vacation and sick time), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, the employee will be in an “at will” position and the Company reserves the right to modify base salary (as well as any other discretionary payments or compensation programs) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
ABOUT US
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 is all about. Join us and be part of something extraordinary.
ABOUT THE TEAM
At BNY, our culture speaks for itself, check out the latest BNY news at BNY Newsroom & BNY LinkedIn
Here’s a Few Of Our Recent Awards
America’s Most Innovative Companies, Fortune, 2025
World’s Most Admired Companies, Fortune 2025
Most Just Companies, Just Capital and CNBC, 2025
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Worksite address
new york city, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.