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 settings.
Ensure code quality through testing, debugging, documentation, and code reviews.
Follow Responsible AI, security, and data governance practices.

Preferred candidate profile
Solid 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 (India)
🏢 Capgemini
📍 India