Corporate Vice President, AI & Data Science

Location Designation: Hybrid - 3 days per week 

Role Overview

As a Corporate Vice President in the Artificial Intelligence & Data (AI&D) organization, you will be a senior technical leader driving New York Life's AI transformation. This is a hands-on, full-stack AI role: you will design, develop, and deliver AI solutions across traditional ML, Generative AI, and Agentic AI, while also shaping technical strategy and mentoring a growing team.

This role will lead the development of AI solutions spanning traditional Machine Learning, Generative AI, and Agentic AI. The role focuses on designing and delivering core technical solutions, shaping enterprise AI practices and standards, and driving end-to-end execution of complex AI initiatives. You will collaborate closely with business stakeholders, data scientists, engineers, product and technology partners, bringing deep expertise in model lifecycle management, responsible AI principles, and New York Life's technology ecosystem.

What You’ll Do:

1. Lead AI/ML and GenAI initiatives end-to-end, in partnership with data, technology, product, and business teams. Scope and shape initiatives from opportunity identification and feasibility assessment through solution design, delivery, and stakeholder alignment.
2. Own the full Model Development Life Cycle (MDLC) from data exploration and feature engineering through model training, validation, deployment, and performance monitoring.
3. Design and implement agentic AI systems, including multi-agent orchestration, tool use, memory architectures, human-in-the-loop checkpoints, and safety guardrails.
4. Design and deploy production-grade RAG and retrieval systems, including hybrid search, reranking, evaluation, and advanced retrieval patterns (agentic RAG, graph-enhanced retrieval) as appropriate.
5. Lead technical decisions across the AI stack: model selection, orchestration frameworks (e.g., LangGraph, LangChain, or direct API integration), cloud AI platforms (GCP, AWS), and data platform (Databricks) integration.
6. Rapidly prototype AI-powered applications and interfaces to validate ideas, test usability, and accelerate adoption, using modern frameworks (Streamlit, React, or similar).
7. Define and evolve technical standards for AI development, including evaluation frameworks, testing practices, observability, and responsible AI principles. Evaluate and integrate emerging AI capabilities (new foundation models, agent frameworks, AI-assisted development tools).
8. Provide technical leadership and mentorship to data scientists and AI engineers, fostering a culture of rapid experimentation, rigorous evaluation, and continuous learning.
9. This role involves limited travel (<10%) to events and vendor meetings

What You’ll Bring:

1. Advanced degree (MS or PhD) in Computer Science, Data Science, Machine Learning, AI, Engineering, Mathematics, Statistics, or a related quantitative field.
2. 8+ years of experience applying data science, ML, and AI to real-world business problems, with progressive growth in scope, complexity, and influence.
3. Full-stack AI fluency: demonstrated ability to work across the spectrum from statistical modeling and ML to LLM application development and agentic system design.
4. Strong software engineering skills in Python and SQL; comfort with modern development practices including version control (Git), testing, code review, CI/CD, and modern data tools (e.g., Databricks, dbt).
5. Deep hands-on experience with LLMs, RAG architectures, prompt engineering, and agentic/orchestration frameworks, particularly LangGraph or equivalent.
6. Experience developing and evaluating AI systems rigorously: automated evaluation pipelines, red-teaming, hallucination detection, safety testing, and performance monitoring.
7. Proficiency with cloud AI platforms, particularly GCP Vertex AI for agentic development, with working knowledge of AWS services (SageMaker, Bedrock). Experience with modern data platforms (Databricks).
8. Familiarity with vector databases, knowledge graphs, and advanced retrieval architectures is a plus.
9. Strong stakeholder engagement and communication skills: ability to scope initiatives, present to senior leaders, manage expectations, and drive alignment across business and technology partners.
10. Track record of mentoring and elevating technical talent.
11. Experience in life insurance, financial services, or other regulated industries is a plus.
12. Experience with AI-assisted development workflows (coding agents, AI pair programming tools) is a plus.

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