Senior Data Scientist - GenAI (LLM, RAG, LangGraph) - Immediate Joiners

Role Overview: We are seeking a highly skilled Senior Data Scientist with hands-on experience in Generative AI to design, build, and deploy advanced AI solutions. This role involves working on cutting-edge projects like RAG-based chatbots, LLM-driven BI systems, and autonomous coding agents. You will collaborate cross-functionally with engineering teams to turn AI prototypes into scalable production systems. Key Responsibilities: Architect and implement end-to-end Generative AI solutions (e.g., RAG chatbots, AI-powered BI tools, code-generating agents) Develop intelligent agents using LangGraph or similar orchestration frameworks Build scalable data ingestion and retrieval pipelines leveraging LlamaIndex and related libraries Design and maintain high-performance vector databases for semantic search and information retrieval Integrate and benchmark multiple LLM providers (OpenAI, Gemini, Claude, etc.) Set up monitoring and observability systems using tools like LangSmith for real-time tracking of AI performance Work closely with engineering teams to productionize machine learning models and applications Required Skills & Qualifications: 3–7 years total experience, with a minimum of 1 year focused on Generative AI Generative AI Expertise: Practical experience with LangGraph or equivalent frameworks for agent orchestration Strong knowledge of LlamaIndex , LangChain , or similar libraries for document processing Proficiency with vector databases (Pinecone, Chroma, Weaviate, etc.) Familiarity with LLM APIs from providers like OpenAI , Anthropic , and Google Hands-on experience with LLM observability tools such as LangSmith, Weights & Biases Demonstrated ability to build natural language to SQL BI tools Proven experience in building RAG systems for contextual chatbot solutions Experience in developing code generation agents and LLM-based programming assistants Traditional AI & Machine Learning: Solid foundation in ML techniques such as classification, regression, clustering, and time-series forecasting Proficiency with frameworks like scikit-learn , TensorFlow , and PyTorch Experience in statistical analysis , A/B testing , and experimental design Strong data handling skills, including feature engineering and preprocessing

Created: 2025-08-05