AI Engineer (LLMs - Agentic AI - Orchestration - RAG)

About the Role :

We are looking for an experienced AI Platform Engineer for our US InsurTech Client to build the Agentic Orchestration Layer powering next-generation intelligent insurance platforms.

This is a hands-on engineering role focused on building enterprise AI agents, multi-agent orchestration workflows, RAG pipelines, context and memory services, and AI tool integrations. You will work on production-grade AI systems integrated with enterprise applications and Guidewire services.

If you have strong hands-on experience building and deploying LLM-powered applications, Agentic AI systems, and enterprise RAG solutions, we would like to hear from you.

Roles & Responsibilities :

• Design and build multi-agent AI systems and orchestration workflows.
• Develop enterprise-grade RAG pipelines and context/memory services.
• Build AI tools, function calling, tool calling, and agent integrations.
• Integrate AI applications with enterprise APIs and Guidewire services.
• Create and maintain prompt libraries, evaluation frameworks, and AI guardrails.
• Optimize AI systems for latency, accuracy, reliability, and inference cost.
• Collaborate with Platform Engineering teams for production deployment and scalability.

Required Skills & Experience :

• Strong programming experience in Python.

• Hands-on experience with FastAPI, REST APIs, and asynchronous programming.

• Strong experience with one or more AI orchestration frameworks such as:

• LangGraph

• LangChain

• Semantic Kernel

• CrewAI / AutoGen

• Strong understanding and hands-on experience with:

• Large Language Models (LLMs)

• Retrieval-Augmented Generation (RAG)

• Embeddings

• Vector databases

• Experience with vector technologies such as Pinecone, OpenSearch, or FAISS.

• Hands-on exposure to Amazon Bedrock, AWS Lambda, API Gateway, and Step Functions.

• Experience in prompt engineering, tool calling, function calling, and structured outputs.

• Working knowledge of Git and Docker.

Nice to Have :

• Guidewire experience.
• Insurance domain knowledge.
• Knowledge Graphs / GraphRAG experience.
• AI Security and Governance experience.

What We Are Looking For

We are particularly interested in engineers who have built real-world, production-grade GenAI applications.

The ideal candidate should be able to demonstrate hands-on experience in areas such as:

• Building end-to-end RAG systems.
• Designing stateful or multi-agent workflows.
• Integrating LLMs with enterprise APIs and external tools.
• Implementing context and memory management.
• Deploying and optimizing AI applications for production environments.
• Improving AI application accuracy, latency, reliability, and cost efficiency.

Interested candidates who can join within 15 days or less are encouraged to apply.