About the job :

Location : Bangalore / Lucknow / Pune

Work Model : Hybrid

Role Type : Full-time, Senior Level

Experience : 4 - 6 Years

Role Overview :

We are looking for a Generative AI / Agentic AI Developer with strong experience in Large Language Models (LLMs), AI Agents, RAG architectures, and intelligent automation systems. The role involves designing, developing, and deploying next-generation AI-powered applications using modern GenAI frameworks and multi-agent architectures. The ideal candidate should have hands-on experience with LLM ecosystems, prompt engineering, AI orchestration frameworks, vector databases, and cloud-based AI deployments. The candidate will work closely with Data Engineering, Product, and AI teams to build scalable AI-driven solutions for enterprise use cases.

Key Responsibilities :

- Design and develop GenAI and Agentic AI applications using LLMs

- Build AI agents, multi-agent workflows, and autonomous task execution systems

- Develop RAG-based pipelines using vector databases and retrieval frameworks

- Integrate LLMs such as OpenAI, Claude, Gemini, Llama, or Mistral into enterprise applications

- Work on prompt engineering, fine-tuning, evaluation, and response optimization

- Build AI-powered assistants, Q&A systems, summarizers, automation bots, and intelligent workflows

- Develop scalable APIs and backend services for AI applications

- Collaborate with Data Engineering and Product teams for AI solution deployment

- Optimize model performance, latency, and cost efficiency

Required Skills :

- Strong proficiency in Python

- Hands-on experience with LLMs and Generative AI frameworks

- Experience with LangChain, LangGraph, CrewAI, LlamaIndex, or similar frameworks

- Strong understanding of RAG architecture and vector databases (Pinecone, ChromaDB, FAISS, Weaviate, etc.)

- Experience with prompt engineering and LLM optimization

- Exposure to multi-agent systems and Agentic AI workflows

- Knowledge of NLP, embeddings, semantic search, and AI orchestration

- Experience with REST APIs, FastAPI, or backend integration

- Exposure to cloud platforms such as AWS, Azure, or GCP

- Understanding of CI/CD, Docker, and deployment workflows