Corporate Vice President - Head of Enterprise AI Platform

New York Life•New York, NY

4d•$147,500 - $211,000•Hybrid

About The Position

We are building a small, senior AI engineering team responsible for creating New York Life's enterprise AI platform—and the first generation of agentic AI solutions that run on it. This team sits at the intersection of AI platform engineering, agentic system design, cloud architecture, and enterprise governance. Our mission is to build secure, governable, production-ready AI capabilities on top of enterprise data, APIs, and cloud-native platform services, moving beyond pilots to scalable business outcomes. As AI Platform Lead, you will define how agentic AI is architected, deployed, secured, evaluated, and scaled responsibly across the enterprise. You will lead the team building the company's AI backbone—the governed platform that powers enterprise AI applications and enables the first wave of agentic insurance solutions. This is a rare opportunity to shape a greenfield platform with executive sponsorship, modern cloud technologies, and a small, highly experienced engineering team. This is a hands-on player-coach role for an engineering leader who enjoys deep technical ownership across the full technology stack—from cloud infrastructure and runtime architecture to tool orchestration, retrieval, memory, evaluation, and agent behavior. You will establish the technical vision, mentor senior engineers, and remain actively involved in architecture, coding, and solution delivery. The platform is built on Google Cloud and designed to leverage cloud-native capabilities while maintaining portability through open architectures and reusable engineering patterns. Success in this role requires balancing innovation with governance, enabling responsible AI adoption in a highly regulated enterprise while delivering measurable business value.

Requirements

Proven experience leading the delivery of enterprise AI platforms, ML platforms, developer platforms, or cloud-native engineering platforms operating at production scale.
Deep expertise with cloud architecture and modern infrastructure, including Google Cloud Platform (preferred), Kubernetes, containers, Infrastructure as Code (Terraform), CI/CD, networking, identity, and observability.
Strong experience designing and building production-grade generative AI and agentic systems, including LLMs, retrieval-augmented generation (RAG), memory architectures, multi-agent orchestration, tool integration, Model Context Protocol (MCP), agent-to-agent (A2A) communication, and evaluation frameworks.
Experience implementing AI governance, security, and responsible AI practices within regulated industries, including AI risk management, runtime guardrails, model controls, privacy, and compliance considerations.
Demonstrated ability to lead senior engineering teams, establish technical direction, influence executive stakeholders, and successfully deliver complex technical roadmaps.
Strong software engineering background with production experience in Python and modern software architecture.
Experience using AI-assisted software development tools such as Cursor, Claude Code, GitHub Copilot, Windsurf, or similar technologies to accelerate engineering productivity.
Excellent communication and collaboration skills with the ability to influence both technical and business stakeholders.

Nice To Haves

Experience building enterprise AI platforms within financial services, insurance, or another highly regulated industry.
Experience with Vertex AI, LangChain, Google ADK, AutoGen, CrewAI, OpenTelemetry, and modern AI platform technologies.
Knowledge of enterprise AI governance frameworks including NIST AI RMF, ISO 42001, SOC 2, HIPAA, GDPR, or emerging AI regulations.
Experience leading greenfield platform initiatives and building high-performing engineering organizations.

Responsibilities

Define the technical vision and reference architecture across the enterprise AI platform, including agent lifecycle services, orchestration capabilities, retrieval and memory services, and AI control plane components that integrate with enterprise AI services.
Own and execute the multi-phase platform roadmap, delivering foundational AI platform capabilities, reusable platform services, enterprise knowledge capabilities, and end-to-end builder agents that accelerate AI solution delivery.
Lead, mentor, and develop a high-performing team of senior AI engineers while maintaining hands-on ownership of architecture, engineering, and agent development. Establish a high engineering bar and champion AI-assisted software development practices.
Partner with Security, Risk, Legal, and enterprise stakeholders to operationalize AI governance, automate solution review processes, and ensure alignment with enterprise AI risk management standards and responsible AI practices.
Drive cloud architecture decisions, build-versus-buy evaluations, and platform portability strategies while leveraging Google Cloud capabilities without creating unnecessary vendor lock-in.
Establish AI FinOps capabilities, including model usage visibility, infrastructure cost attribution, dashboards, and budget guardrails that enable responsible scaling across the enterprise.
Partner with business and technology leaders to deliver the first generation of enterprise agentic AI solutions that demonstrate measurable business outcomes.
Build agents that improve the platform itself while leveraging AI-assisted engineering throughout the software development lifecycle.