Senior Data Scientist - Agentic AI & LLMs

Job Title : Senior Data Scientist Agentic AI, LLMs & RAG Location: Delhi NCR (Gurugram/Noida) & Bengaluru Type: Permanent Full-Time Experience: 4+ Years About the Role We are seeking a highly skilled Senior Data Scientist with expertise in Agentic AI, Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) . The ideal candidate will be responsible for building intelligent AI agents, developing enterprise-grade GenAI solutions, and deploying scalable AI systems that drive business transformation and automation. Mandatory Skills 4+ years of experience in Data Science , Machine Learning , or Artificial Intelligence Strong proficiency in Python Hands-on experience with LLMs (GPT, Claude, Gemini, Llama, Mistral, etc.) Experience building RAG -based applications Expertise in Agentic AI f rameworks such as LangGraph , CrewAI , AutoGen , or similar Strong Prompt Engineering skills Experience with Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate, Milvus, etc.) Strong understanding of NLP and Machine Learning concepts Proficiency in SQL Experience deploying AI/ML applications in production Exposure to AWS, Azure, or GCP Role & Responsibilities Design, develop, and deploy Agentic AI and Generative AI solutions. Build intelligent AI agents capable of reasoning, planning, and autonomous task execution. Develop and optimize RAG pipelines for enterprise-scale applications. Integrate LLMs with enterprise systems, APIs, and knowledge bases. Implement vector search and embedding-based retrieval systems. Engineer prompts and optimize LLM performance for business use cases. Evaluate, benchmark, and improve GenAI application performance. Collaborate with cross-functional teams to identify AI-driven opportunities. Ensure scalability, reliability, security, and governance of AI solutions. Stay updated with advancements in Agentic AI, LLMs, and emerging AI technologies. Preferred Skills Experience with LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel Knowledge of LLM fine-tuning, LoRA, PEFT, and model optimization Experience with Docker, Kubernetes, and MLOps practices Exposure to AI observability and evaluation frameworks Experience building AI Assistants, Copilots, Chatbots, or Autonomous Agent Systems