About the Role :

We are looking for an experienced AI 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.
- Solid 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.

Note : Interested candidates who can join within 15- 30 days are encouraged to apply.

Role: NLP / DL Engineering / Architect, Industry Type: Emerging Technologies (AI/ML), Department: Data Science & Analytics, Employment Type: Full Time, Permanent Role Category: Data Science & Machine Learning Education UG: B.Sc in Data Science, Artificial Intelligence and Data Science, Artificial Intelligence and Machine Learning, Computer Science and Technology, B.Tech / B.E. in Electronics and Telecommunication Engineering, Computer Science and Business System, Instrumentation and Control Engineering, Artificial Intelligence And Machine Learning, Electronics, Applied Electronics And Instrumentation, Computer Science and Engineering (CSE), Electronics and Communication Engineering (ECE), Information Technology, Artificial Intelligence And Data Science, Electronics And Computer Engineering, Robotics and Automation Engineering PG: M.Tech in Electronics/Telecommunication, Artificial Intelligence and Machine Learning, Computers Key Skills Skills highlighted with ‘‘ are preferred keyskills LangchainLanggraphLarge Language ModelRetrieval Augmented GenerationAgentic Ai PythonCrewaigenerative aiAWS BedrockFAISSFast APIPineconesemantic kernelGuidewiretool callinggraph RAG

📌 AI Engineer - Generative AI & Agentic AI (Bengaluru)
🏢 Knowledge Foundry
📍 Bengaluru