Senior Associate - Python AI Developer

Location Designation: Hybrid - 3 days per week

Business Unit

Technology, Data, AI and Ventures (TDAV)

Within the Tech, Data, AI, Ventures (TDAV) organization, our work is guided by a shared vision: deploying the power of technology, data, AI and ventures to accelerate sustainable competitive advantage for New York Life’s businesses. We build solutions that power how we serve policy owners, agents, advisors and employees while delivering measurable business outcomes.

Across technology, data, AI, cyber, product, digital experience, architecture and infrastructure, TDAV combines the scale and investment of an industry leader, access to leading-edge technologies and the opportunity to help shape how a world-class financial services company competes in the AI era — all backed by the stability and purpose of a mutual company built to last.

Department: Corporate Functions Technology

Role Overview

Corporate Functions Technology is building the next generation of AI-enabled applications that support our corporate business units - Legal, Compliance, Risk Management, and other core functions of the enterprise. We are seeking a Python AI Developer to design, build, and operationalize AI features and a reusable enterprise AI/agent services layer that integrates with our existing enterprise application ecosystem.

What You’ll Do

• Design and build Python-based AI services (LLM integrations, retrieval-augmented generation, agentic and human-in-the-loop workflows, embeddings/vector search) that expose clean APIs for consumption by existing enterprise applications.
• Design and implement this reusable enterprise AI/agent services layer - a shared set of agent orchestration services, tools, guardrails, and interfaces that applications across Corporate Functions can build on, rather than each team solving agent design independently.
• Partner directly with Enterprise Developers to integrate AI capabilities into existing platforms, defining contracts (REST/gRPC/messaging), data flows, and shared services between the Python AI services layer and application layer.
• Implement guardrails, human oversight mechanisms, monitoring, and evaluation pipelines to ensure AI outputs are accurate, explainable, auditable, and safe for use in a regulated environment.
• Collaborate with Compliance, Risk, Legal, and Model Risk Management stakeholders to ensure AI features meet internal model governance standards and external regulatory expectations (e.g., state insurance regulations, NAIC guidance, SR 11-7-style model risk frameworks, data privacy requirements).
• Build and maintain data pipelines and integrations connecting AI services to internal systems of record, ensuring appropriate handling of sensitive policyholder, HR, and financial data.
• Write production-quality, well-tested, well-documented Python code and contribute to CI/CD pipelines, observability, and operational readiness for AI services.
• Participate in architecture reviews, security reviews, and model validation exercises as part of the enterprise AI governance process.
• Stay current on the evolving AI/ML and agentic tooling landscape and bring forward recommendations for responsible adoption within a highly regulated environment.

What You’ll Bring

Required Skills

• 4+ years of professional software development experience, with strong hands-on Python skills in an enterprise environment.
• Demonstrated experience building applications or services using LLMs - e.g., prompt engineering, RAG pipelines, embeddings/vector databases, function/tool calling, or agent frameworks.
• Hands-on experience evaluating and testing LLM-based applications, including designing representative test sets, defining quality and safety metrics, performing regression testing, and/or implementing automated evaluation pipelines.
• Experience with Model Context Protocol (MCP), including building MCP servers, defining tools/resources, integrating MCP clients, and securely connecting AI agents to enterprise systems and APIs.
• Experience designing and consuming REST APIs and integrating services across different technology stacks - direct experience partnering with or integrating into Java-based systems is highly valued.
• Solid understanding of software engineering fundamentals: version control, testing, CI/CD, code review, and secure coding practices.
• Experience working with cloud platforms (GCP and/or AWS) and containerized deploymen…