Job Title : Generative AI / Agentic AI Engineer
Location : Pune
Experience : 5+Years
Job Description :
We are seeking a highly skilled Generative AI / Agentic AI Engineer to design, develop, and deploy enterprise-grade AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Multi-Agent Systems. The ideal candidate should have strong expertise in NLP, Prompt Engineering, Agentic AI frameworks, and production-scale AI application development.
Key Responsibilities :
- Design and develop Generative AI applications using LLMs and modern AI frameworks.
- Build and optimize RAG and GraphRAG solutions for enterprise knowledge retrieval.
- Develop Agentic AI workflows and Multi-Agent Systems using frameworks such as LangGraph, CrewAI, AutoGen, or similar.
- Create and optimize prompts, tool-calling workflows, and agent orchestration pipelines.
- Integrate LLMs with enterprise data sources, APIs, vector databases, and knowledge graphs.
- Develop scalable backend services and APIs using Python and FastAPI.
- Evaluate, monitor, and improve AI model performance, response quality, and reliability.
- Collaborate with cross-functional teams to translate business requirements into AI-powered solutions.
- Deploy and maintain AI applications on cloud platforms such as Azure, AWS, or GCP.
Mandatory Skills :
- 2+ years of hands-on experience in Generative AI / LLM development.
- 3+ years of experience in Natural Language Processing (NLP).
- Strong proficiency in Python.
- Hands-on experience with Large Language Models (LLMs).
- Strong experience with Prompt Engineering.
- Experience with RAG (Retrieval-Augmented Generation).
- Experience building Agentic AI workflows.
- Experience with Multi-Agent Systems.
- Hands-on experience with LangChain and LangGraph.
- Experience integrating AI solutions with vector databases and enterprise data sources.
Preferred Skills :
- GraphRAG, Knowledge Graphs, or Neo4j.
- CrewAI, AutoGen, Google ADK, or similar agent frameworks.
- MCP (Model Context Protocol).
- Vector Databases : Pinecone, ChromaDB, FAISS, Qdrant, Weaviate.
- OpenAI, Azure OpenAI, AWS Bedrock, Gemini.
- LangSmith, LangFuse, or AI observability tools.
- FastAPI, Docker, Kubernetes, CI/CD.
- Fine-tuning, LoRA, QLoRA.
Education :
- Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
(ref:hirist.tech)