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 frameworks 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