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. .