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# Senior Associate - Full-Stack AI Engineer

- **Company:** New York, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $100,000.0 - $143,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Frameworks, Automated Storage and Retrieval Systems, Continuous Integration, Programming Tools, Distributed Systems, Python (Programming Language), Knowledge-Based Systems, Search Technologies, Software Deployment, Software Engineering, Workflow Management Systems, Google Cloud, Spring Cloud, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Deployment Automation, Machine Learning Operations
- **Published:** August 29, 2026
- **Apply:** https://www.careerjet.com/job/us95204f7e7b3a607654952661c6939795/eaa

## About the Role

* 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 agentframeworks.
 * 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.

## Description

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 AIstrategy.
You will contribute across the AI engineering stack, building scalable platform services and production-ready agentic solutions while helping establish engineeringstandards, reusable frameworks, and operational best practices.
What You'll Do

 * Design, build, and enhance enterprise AI platform capabilities, including model and agent lifecycle services, orchestrationframeworks, 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 retrievaltechniques.
 * 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 performanceoptimization.
 * 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.


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