Associate AI Engineer

GREATER NEW YORK MUTUAL INSURANCE COMPANY•Edison, NJ

1d•Hybrid

About The Position

The position is responsible for designing, building, deploying, and maintaining enterprise-grade Agentic AI solutions under the direction of an Sr. AI Engineer. This role focuses on implementing autonomous and semi-autonomous AI agents using large language models (LLMs), orchestration frameworks, and Azure-native AI services. The position supports intelligent automation initiatives across Insurance business domains by translating product requirements into scalable, secure, and observable AI systems.

Requirements

Bachelor’s Degree in Computer Science, Engineering, or related field required.
1–3 years of experience in AI/ML engineering, data engineering, or software engineering required.
Hands-on experience with LLMs, GenAI, or intelligent automation systems required.
Experience building AI solutions on cloud platforms, preferably Microsoft Azure required.
Strong proficiency in Python and AI/ML libraries.
Hands-on experience with: LLMs, prompt engineering, and RAG architectures, Vector databases and semantic search, Agent orchestration frameworks
Experience with Microsoft Azure, including: Azure OpenAI, Azure Functions, Logic Apps, AKS
Knowledge of API development and system integration.
Familiarity with CI/CD pipelines, Git-based version control, and Agile delivery.
Strong analytical, troubleshooting, and communication skills.

Nice To Haves

Exposure to Agentic AI, workflow orchestration, or multi-agent systems preferred.
Azure AI Fundamentals or equivalent certification preferred.
Familiarity with data privacy, security, and compliance in AI development.
Exposure to prompt engineering and GenAI tools a plus.
Insurance domain exposure preferred.

Responsibilities

Design, develop, and deploy Agentic AI systems based on product requirements defined by the Business SMEs.
Implement agent workflows including: Planning, execution, validation, and retry logic, Tool and API invocation, Context and memory management
Build and maintain LLM-powered pipelines, including RAG-based architectures.
Integrate AI agents with enterprise systems using APIs, event-driven workflows, and automation services.
Develop and manage data ingestion and enrichment pipelines for structured and unstructured data.
Monitor AI system performance, accuracy, latency, and cost; implement optimizations and improvements.
Implement guardrails, safety mechanisms, and human-in-the-loop controls.
Support production deployment using Azure-native services and CI/CD pipelines.
Document system architecture, workflows, prompts, and operational runbooks.
Collaborate with product managers, architects, and data teams to iterate on AI solutions.
Participate in special projects and perform additional duties as required.