Experience: 5–8 Years

Work Mode: Remote

Duration: 6+ Months Contract

Timezone: 2 PM – 11 PM IST

We are looking for a GenAI Engineer with strong hands-on experience in building production-grade LLM, RAG and Agentic AI solutions. The candidate should have experience designing AI systems that can understand enterprise data, use external tools/APIs, and autonomously execute multi-step workflows.

Key Responsibilities Design and develop RAG-based GenAI applications using LLMs.

Build Agentic AI workflows with tool calling, planning and multi-step reasoning.

Work with OpenAI / Azure OpenAI / Anthropic / Gemini or similar LLMs.

Develop document ingestion, chunking, embedding and retrieval pipelines.

Hands-on with vector databases such as Pinecone, Weaviate, Milvus, Qdrant or FAISS.

Implement advanced retrieval techniques including hybrid search, reranking and query expansion.

Develop AI agents using frameworks such as LangGraph, LangChain, LlamaIndex or Semantic Kernel.

Integrate GenAI applications with enterprise REST APIs, databases and third-party tools.





Implement prompt engineering, structured outputs, function/tool calling and guardrails.

Develop evaluation frameworks for RAG accuracy, hallucination, relevance and response quality.

Optimize LLM applications for latency, scalability and token/cost efficiency.

Deploy GenAI solutions using Python, Docker and cloud platforms such as Azure/AWS/GCP.

Must-Have Skills Python

LLMs / Generative AI

RAG architecture

Agentic AI / AI Agents

LangGraph / LangChain

Vector Databases

Embeddings & Semantic Search

Prompt Engineering

REST APIs

Azure OpenAI / OpenAI

Cloud deployment

GenAI evaluation & observability

Valuable To Have MCP (Model Context Protocol)

Multi-agent systems

Knowledge Graph / Graph RAG

Azure AI Search

Fine-tuning / LoRA

AI safety & guardrails

LangSmith / Arize / MLflow

Skills: python,rag,agentic ai,cloud deployment,langgraph/langchain

📌 GenAI / Agentic AI Engineer - RAG & LLM (India)
🏢 Orbion Infotech
📍 India