Senior Associate - Full-Stack AI Engineer

New York Life•New York, NY

4d•$100,000 - $143,000•Hybrid

About The Position

As a Senior Associate - Full-Stack AI Engineer, you will independently design and deliver platform capabilities and intelligent applications that support New York Life's enterprise AI strategy. You will contribute across the AI engineering stack, building scalable platform services and production-ready agentic solutions while helping establish engineering standards, reusable frameworks, and operational best practices.

Requirements

3-5 years of software engineering experience.
Strong proficiency in Python and experience with modern software development frameworks.
Experience building cloud-native applications, APIs, distributed systems, or platform services.
Hands-on experience with generative AI technologies, including LLMs, RAG, tool integration, prompt engineering, and/or agent frameworks.
Experience with GCP, Kubernetes, Infrastructure as Code, and CI/CD practices.
Ability to independently own initiatives from design through production deployment.
Strong communication and stakeholder partnership skills.

Responsibilities

Design, build, and enhance enterprise AI platform capabilities, including model and agent lifecycle services, orchestration frameworks, developer tooling, runtime services, and governance features.
Build production-ready agentic AI solutions that leverage multi-agent architectures, tool integration, planning frameworks, retrieval systems, memory, and workflow orchestration.
Design and implement enterprise knowledge systems using RAG, semantic search, embeddings, vector databases, and modern retrieval techniques.
Develop secure cloud-native services using Google Cloud Platform, Kubernetes, Infrastructure as Code, and CI/CD practices.
Implement MLOps and LLMOps capabilities, including deployment automation, evaluation, monitoring, observability, and performance optimization.
Partner with business and technology stakeholders to deliver AI solutions that address real business challenges.
Contribute to engineering standards, architecture reviews, and operational excellence initiatives.
Leverage AI-assisted engineering capabilities throughout the software development lifecycle.