Senior Vice President, AI / ML Software Engineer

Posted 5 Hours Ago
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New York, NY, USA
In-Office
Senior level
Fintech • Financial Services
The Role
Lead architecture and delivery of production-grade agentic AI and RAG systems. Own multi-agent orchestration, embedding/vectorization pipelines, retrieval, evaluation frameworks, and team leadership for engineers building document-intelligence and AI-assisted developer tooling. Responsible for production delivery, observability, CI/CD, and cross-team integration in an enterprise finance environment.
Summary Generated by Built In

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.

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’re seeking a future team member for the role of Senior Vice President AI/ML Software Engineer  to lead the architecture and delivery of production-grade AI systems built on agentic frameworks, retrieval-augmented generation (RAG), and LLM orchestration. This is a hands-on technical leadership role responsible for a team of engineers building autonomous AI pipelines that extract, validate, and reason over complex unstructured documents. You will own the technical vision for a multi-agent ecosystem -- designing pipeline orchestration engines, embedding/vectorization strategies, knowledge retrieval systems, and AI-assisted code generation tooling. You will lead a VP-level engineer and a broader team of 4-8 developers. 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:

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. 

BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.

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.



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 #LifeAtBNY 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

    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.

    BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.

    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.

    Skills Required

    • Bachelor's or advanced degree in computer science, engineering, or related discipline (or equivalent experience)
    • 10+ years professional software engineering experience
    • 3+ years leading or technically mentoring engineering teams
    • Deep expertise in AI/ML systems including LLM orchestration, prompt engineering, and chain-of-thought reasoning
    • Design and implementation experience with RAG architectures: chunking, embedding, retrieval, re-ranking, context assembly
    • Knowledge of agentic patterns (ReAct, tool-use, planning loops, multi-agent coordination)
    • Experience with vector databases and embedding models (FAISS, Pinecone, Weaviate, OpenAI embeddings, sentence-transformers)
    • Strong Python (3.11+) with FastAPI, async/await, Poetry, Pydantic, and pytest
    • Solid Java experience (Java 21, Spring Boot 3.x), microservice architecture
    • Production AI delivery experience: observability, error recovery, audit trails for real workloads
    • Document intelligence experience: OCR pipelines, NLP, structured extraction from unstructured text
    • Testing and evaluation expertise: golden-truth validation, retrieval metrics (MRR, NDCG), extraction F1 scores
    • Enterprise architecture skills: API design, circuit breakers, caching, event-driven patterns
    • Experience building custom agent frameworks (not just configured off-the-shelf)
    • Knowledge of graph-based retrieval, knowledge graphs, and entity-relationship extraction
    • Experience with AI-assisted developer tooling, code generation pipelines, automated refactoring
    • Familiarity with model fine-tuning approaches (LoRA/QLoRA) or RLHF
    • Experience with evaluation-driven development: automated prompt regression testing, A/B 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

    BNY Compensation & Benefits Highlights

    The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about BNY and has not been reviewed or approved by BNY.

    • Healthcare Strength Health coverage includes comprehensive options with a $0‑premium plan for eligible lower earners, expanded mental‑health support with personalized therapy, and strong income protection through short‑ and long‑term disability. These features have been recently enhanced and are paired with dental and vision coverage.
    • Parental & Family Support Parental leave provides 16 weeks of fully paid time for all parents, with added support such as adoption assistance. This breadth offers strong coverage for major family events.
    • Retirement Support The 401(k) program includes a company match and Roth options to support long‑term savings. Additional financial programs like tuition assistance and savings vehicles complement retirement readiness.

    BNY Insights

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    The Company
    HQ: New York, NY
    41,739 Employees

    What We Do

    We help make money work for the world — managing it, moving it and keeping it safe. As a leading global financial services company at the center of the world’s financial system, we touch nearly 20% of the world’s investable assets. Today we help over 90% of Fortune 100 companies and nearly all the top 100 banks globally access the money they need. For 240 years we have partnered alongside our clients to create solutions that benefit businesses, communities and people everywhere.

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