Role & responsibilities
- Develop and enhance Generative AI applications using LLMs and AI frameworks.
- Build and optimize RAG pipelines, vector search, and AI-powered workflows.
- Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
- Develop REST APIs and integrate AI capabilities into enterprise applications.
- Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
- Ensure code quality through testing, debugging, documentation, and code reviews.
- Follow Responsible AI, security, and data governance practices.

Preferred candidate profile
- Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
- Valuable understanding of Data Structures & Algorithms,



complexity analysis, and problem-solving.
- Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
- Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
- Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
- Experience with PyTorch, TensorFlow, or Keras.
- Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
- Understanding of AI governance, data privacy, and Responsible AI principles.

📌 Capgemini Looking For Gen Ai/Agentic Ai For Pune (Bengaluru)
🏢 Capgemini
📍 Bengaluru