Job Summary Job Title: Python Developer - Agentic AI / LLM / RAG Engineer
Job Level: JL3 / JL4 (Based on Experience) 1-6 Yrs
Location: Bangalore/ Pune
We are seeking a skilled Python Developer with expertise in Agentic AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to design, develop, and deploy intelligent AI solutions. The candidate will be responsible for building AI agents, integrating LLM-powered applications, implementing RAG architectures, and optimizing AI workflows for enterprise use cases.
Responsibilities
- Develop and maintain AI applications using Python.
- Design and implement Agentic AI systems using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
- Build and optimize RAG pipelines using vector databases and retrieval frameworks.
- Integrate and fine-tune Large Language Models (LLMs) including OpenAI, Azure OpenAI, Llama, Claude, Gemini, or similar.
- Develop APIs and microservices for AI applications.
- Implement prompt engineering, workflow orchestration, and AI agent collaboration patterns.
- Create scalable solutions using cloud platforms such as Azure, AWS, or GCP.
- Monitor, evaluate, and improve AI model performance, accuracy, and response quality.
- Collaborate with business and technology teams to translate requirements into AI-driven solutions.
Technical Requirement
- Strong programming experience in Python.
- Hands-on experience with LLMs, Generative AI, Agentic AI, and RAG architectures.
- Experience with LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, or equivalent frameworks.
- Knowledge of vector databases such as Pinecone, ChromaDB, Weaviate, FAISS, or Azure AI Search.
- Experience with REST APIs, FastAPI, Flask, or Django.
- Understanding of embeddings, semantic search, prompt engineering, and model evaluation.
- Experience with Git, CI/CD, and software development best practices.
- Knowledge of cloud AI services (Azure OpenAI preferred).
Preferred Skills
- Experience with multi-agent architectures and AI orchestration.
- Knowledge of MLOps, model deployment, and containerization (Docker/Kubernetes).
- Exposure to NLP, machine learning, and deep learning concepts.
- Experience with enterprise AI governance, security, and responsible AI practices.
Additional Responsibility Technology Stack
- Technology | Artificial Intelligence Automation
- Skill Category | Python Development, Agentic AI, LLM, RAG, Generative AI
- Primary Skills | Python, LangChain, LangGraph, CrewAI, Azure OpenAI, RAG, Vector Databases
- Secondary Skills | FastAPI, Docker, Kubernetes, Azure AI Search, MLOps
Educational Requirement
Bachelor of Engineering
Service Line
Cloud Infrastructure Services
