Description :

Position : Data Scientist with Prompt Engineering

Experience : 4 to 7 Years

Location : Pune (Hybrid - Viman Nagar) & Remote

Notice Period : Immediate to 10 days

Role Overview :

We are seeking a highly motivated Data Scientist specializing in Generative AI and NLP with strong client-facing experience. The ideal candidate will have hands-on expertise in RAG applications, prompt engineering, and agentic AI frameworks, along with a solid foundation in traditional and modern NLP techniques.

You will partner with clients to define business problems, design advanced AI/ML solutions, and deliver production-ready systems leveraging state-of-the-art Generative AI technologies.

Key Responsibilities :

- Collaborate with clients to understand business goals and problem statements.

- Design, develop, and deploy RAG applications to enhance knowledge retrieval and improve response generation.

- Work with frameworks such as LangChain, LangGraph, LlamaIndex, or similar to build scalable GenAI workflows.

- Apply prompt engineering strategies to optimize LLM performance and outputs.

- Leverage agentic AI concepts to design multi-step reasoning and autonomous decision-making workflows.

- Develop and fine-tune NLP/GenAI models for tasks such as summarization, Q&A, entity extraction, conversational AI, etc.

- Write clear, logical, and structured chains of thought when approaching problem-solving to ensure transparency and reproducibility.

- Collaborate with cross-functional teams to integrate GenAI/NLP solutions into client environments.

- Stay updated with the latest advancements in LLMs, GenAI, and NLP.

Required Skills & Qualifications :

- 4-7 years of experience in Data Science, AI/ML, NLP, or GenAI projects.

- Strong client-facing experience with excellent communication and presentation skills.

- Hands-on expertise in RAG architectures and frameworks (LangChain, LangGraph, LlamaIndex, etc.).

- Proficiency in prompt engineering and LLM-based application development.

- Knowledge or practical exposure to agentic AI applications (multi-agent workflows, autonomous systems).

- Strong foundation in NLP techniques (tokenization, embeddings, sentiment analysis, named entity recognition, etc.).

- Solid programming skills in Python and familiarity with ML/AI libraries (PyTorch, TensorFlow, Hugging Face).

- Experience with vector databases (Pinecone, FAISS, Weaviate, Chroma, etc.).

- Familiarity with cloud platforms (AWS, Azure, GCP) and deployment pipelines.

- Analytical problem-solving mindset with the ability to write structured reasoning steps.