We are looking for a hands-on AI Engineer to help build our foundational AI infrastructure from the ground up. The ideal candidate will have solid experience in Python, LangChain, Agentic AI, RAG, vector databases, and LLM applications .

You will design, develop, evaluate, and deploy intelligent applications with a strong focus on Agentic AI and Retrieval-Augmented Generation (RAG) systems.

Key Responsibilities

- Design and develop production-ready RAG architectures and Agentic AI workflows.
- Build robust data ingestion and processing pipelines for unstructured and semi-structured data.
- Work with web crawlers, OCR technologies, document parsing, and Docling to extract and structure information.
- Develop LLM-powered applications using Python and LangChain.
- Build and integrate AI agent tools using Model Context Protocol (MCP).
- Implement vector databases, embeddings, semantic search, and retrieval pipelines.
- Evaluate and benchmark LLM/RAG applications using Ragas and other evaluation techniques.
- Perform prompt engineering, response evaluation, and optimization to improve accuracy and relevance.
- Design scalable and maintainable AI solutions suitable for production environments.
- Collaborate with engineering teams to define AI architecture, development standards, and best practices.




- Contribute to technical decisions in a greenfield AI environment and help establish the organization's AI technology foundation.

Required Skills

- Strong proficiency in Python.
- Hands-on experience with LangChain.
- Strong experience building Agentic AI / AI Agent systems.
- Deep understanding of RAG architecture and LLM application development.
- Experience with Vector Databases, embeddings, semantic search, and retrieval techniques.
- Experience with Ragas or LLM evaluation frameworks.
- Strong knowledge of Prompt Engineering.
- Hands-on experience with OCR, document parsing, Docling, and web crawling.
- Understanding of MCP (Model Context Protocol) and agent tool integration.
- Experience working with LLMs, APIs, and AI application development.

Nice to Have
- Experience deploying ML/AI models into production.
- Experience with AWS, GCP, or Azure.
- Knowledge of Docker, Kubernetes, CI/CD, and MLOps.
- Experience with additional LLM frameworks such as LlamaIndex, LangGraph, or Hugging Face.
- Experience working with databases such as PostgreSQL, MongoDB, or vector databases.

Key Skills Python | LangChain | Agentic AI | RAG | Vector Database | LLM | Ragas | MCP | Prompt Engineering | OCR | Docling | Web Crawling Skills: prompt,vector,ocr,python

📌 AI Engineer_5+ years (Kolkata Metropolitan Area)
🏢 Zorba AI
📍 Kolkata Metropolitan Area