SVP, AI/ML Software Engineer - New York City

Salary: $30,000 - 55,000 per year Requirements:

• We require a bachelors degree, an advanced degree in computer science, engineering, or a related field, or equivalent professional experience.
• We are looking for 10+ years of software engineering experience.
• We need 3+ years of experience leading or technically mentoring engineering teams.
• We seek deep expertise in AI/ML systems, including LLM orchestration, prompt engineering, chain-of-thought reasoning, RAG architectures, and agentic patterns.
• We need experience with vector databases and embedding models such as OpenAI embeddings, sentence-transformers, FAISS, Pinecone, Weaviate, or similar tools.
• We are looking for strong Python skills, including Python 3.11+, FastAPI, async/await, Poetry, Pydantic, and pytest.
• We need solid Java experience, including Java 21, Spring Boot 3.x, and microservice architecture.
• We expect production AI delivery experience with observability, error recovery, and audit trails.
• We require experience with document intelligence, including OCR pipelines, NLP, and structured extraction from unstructured text.
• We are looking for testing and evaluation experience, including golden-truth validation, retrieval metrics, extraction F1 scores, and agent success rates.
• We value enterprise architecture experience, including API design, circuit breakers, caching, and event-driven patterns.
• Preferred experience includes building custom agent frameworks, knowledge graphs, code AI tooling, model fine-tuning, evaluation-driven development, Angular/TypeScript, capital markets, and enterprise AI governance.

• We lead the architecture and delivery of production-grade AI systems built on agentic frameworks, RAG, and LLM orchestration.
• We architect multi-agent AI systems, including tool-use patterns, planning and reasoning loops, and autonomous decision chains.
• We design and evolve RAG infrastructure, covering chunking strategies, embedding pipelines, vector store selection, retrieval ranking, and context optimization.
• We define vectorization strategy, including embedding model selection, dimensionality trade-offs, hybrid search, and re-ranking approaches.
• We own the AI pipeline orchestration framework, including blocks, inlets/outlets, blackboards, memory stores, and content policy enforcement.
• We make build-versus-buy decisions across the AI toolchain.
• We establish scalable prompt engineering practices, including prompt versioning, chain-of-thought decomposition, few-shot management, and guardrails.
• We design multi-agent architectures with shared memory and inter-agent communication protocols.
• We build autonomous extraction agents that can plan, select tools, self-correct, and validate outputs.
• We implement knowledge graph construction from unstructured documents, including entity extraction, relationship mapping, and graph-based retrieval.
• We develop evaluation frameworks for retrieval precision and recall, extraction accuracy, task completion, and hallucination detection.
• We design feedback loops using human-in-the-loop correction, golden-truth datasets, and continuous prompt refinement.
• We lead, mentor, and grow a team of 4-8 engineers, including direct management of a VP-level AI engineer.
• We drive architecture reviews, design sessions, and technical decision-making.
• We own sprint planning, technical backlogs, and delivery commitments.
• We implement core agentic components such as agent loops, tool registries, memory persistence, and reasoning traces.
• We build embedding pipelines, including document preprocessing, chunk boundary detection, metadata enrichment, and vector index management.
• We develop scoring and validation systems, including Bayesian confidence, cross-agent consensus, and golden-truth comparison.
• We contribute to platform services in Java/Spring Boot and to the AI service layer in Python/FastAPI.
• We build AI-assisted developer tooling, including code generation workflows, automated test generation, and intelligent code review.
• We own CI/CD pipelines, containerized deployments, and environment promotion.
• We define observability for agent execution traces, token usage, retrieval quality metrics, and pipeline telemetry.
• We manage schema evolution and data stores across relational and vector systems.
• We coordinate cross-team dependencies with platform engineering, data engineering, and infrastructure teams.

• AI
• API
• Angular
• Architect
• CI/CD
• Embedding Models
• FastAPI
• Fine-tuning
• Java
• LLM
• Python
• RAG
• Spring
• Spring Boot
• TypeScript
• pytest
• Agentic AI
• Azure
• Backend
• Cloud
• D3
• Docker
• Frontend
• GitLab
• Support
• Maven
• Oracle
• PostgreSQL
• React

More:

We are BNY, a leading global financial services company at the center of the global financial system, influencing nearly 20% of the worlds investible assets. Our culture supports better business performance and employee growth, and we bring together bold ideas, advanced technology, and exceptional talent to deliver transformative solutions for clients worldwide. This Senior Vice President AI/ML Software Engineer role is based in New York, NY and is a hands-on technical leadership position focused on building production-grade AI systems. We offer highly competitive compensation, benefits, and wellbeing programs, along with flexible global resources, generous paid leave, and paid volunteer time. We are also an Equal Employment Opportunity/Affirmative Action employer.

last updated 40 week of 2026