Data Scientist +gen AI+prompt engineering+RAG (Gurugram)

Data Scientist (Generative AI) Job Title: Data Scientist Generative AI (GenAI) Location: Hybrid Employment Type: Full-Time Noitice Period : Only Aug Joiners , 15 days Job Summary We are seeking a highly skilled Data Scientist Generative AI with strong expertise in Data Science, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG). The ideal candidate should have hands-on experience in designing, developing, and deploying GenAI solutions to solve real-world business problems. Strong communication and stakeholder management skills are essential. Key Responsibilities - Design, build, and deploy Generative AI applications using LLMs. - Develop and optimize RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases. - Create, evaluate, and optimize prompts to improve LLM performance. - Apply Data Science and Machine Learning techniques to solve complex business challenges. - Fine-tune and evaluate AI models for accuracy, scalability, and efficiency. - Work closely with business stakeholders to understand requirements and translate them into AI solutions. - Integrate GenAI solutions with enterprise applications and data sources. - Stay updated with the latest advancements in Generative AI, LLMs, and AI frameworks. Required Skills - Strong hands-on experience in Data Science. - Practical experience with Generative AI and Large Language Models (LLMs). - Solid expertise in Prompt Engineering. - Experience building RAG (Retrieval-Augmented Generation) solutions. - Proficiency in Python and AI/ML libraries. - Experience with vector databases and embedding models is preferred. - Strong analytical and problem-solving skills. - Excellent verbal and written communication skills. Preferred Skills - Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks. - Knowledge of OpenAI, Azure OpenAI, Anthropic, or Google Gemini models. - Experience with vector databases such as Pinecone, FAISS, ChromaDB, or Milvus. - Exposure to cloud platforms such as Azure, AWS, or GCP. .