Python Developer

Mandatory Skills

Docker ,AI Agents and AI Orchestration and RAGAS ,AWS

Django, Fast API ,Generative AI / LLMs

LangChain / LlamaIndex , LangGraph / Google ADK, LLM APIs

Postgres / MongoDB / SQL ,Prompt Engineering ,Python

RAG (Retrieval-Augmented Generation) ,REST APIs

Vector Databases

Project Highlights

• Work on cutting-edge Generative AI solutions using LLMs, RAG, and AI agents tobuild scalable, intelligent applications.
• USP
• Hands-on exposure to GenAI, LLMs, and AI agents.
• Opportunity to build production-ready AI solutions using modern frameworks and cloud technologies.

Roles and Responsibilities

• Design, develop, and deploy Generative AI and LLM-based applications using Python.
• Integrate LLM APIs such as OpenAI, Gemini, and Claude into AI-powered solutions.
• Develop and optimize RAG pipelines using vector databases and embedding-based retrieval.
• Build AI agents and orchestration workflows using LangChain, LangGraph, LlamaIndex, or Google ADK.
• Implement prompt engineering, context management, and LLM evaluation techniques.
• Work with vector databases such as Qdrant, Pinecone, and FAISS.
• Develop REST APIs using FastAPI or Django and implement real-time communication using SSE or WebSockets.
• Integrate MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication where required.
• Manage data processing, ETL pipelines, and database integrations.
• Implement MLOps practices, LLM evaluation, and performance monitoring.
• Use Git, GitHub, Docker, and cloud platforms such as AWS or Azure for deployment and development.

Requirements

• Strong proficiency in Python and hands-on experience in Generative AI / LLMs.
• Experience with LLM APIs such as OpenAI, Gemini, and Claude.

Strong understanding of Prompt Engineering, RAG, and vector databases (Qdrant,Pinecone, FAISS).

• Hands-on experience with LangChain, LlamaIndex, LangGraph, or Google ADK.
• Experience building AI Agents, AI Orchestration workflows, and RAG pipelines.
• Knowledge of MCP, A2A, and LLM evaluation frameworks such as RAGAS.
• Experience developing REST APIs using FastAPI or Django.
• Familiarity with SSE, WebSockets, PostgreSQL, MongoDB, and SQL.
• Experience in data processing, ETL, MLOps, and LLM evaluation.
• Proficiency in Git/GitHub and Docker.
• Exposure to cloud platforms such as AWS or Azure