Advance your career as a Python GenAI Engineer with Capgemini, a global leader in business and technology transformation. Empowering you to shape your professional path, we offer a collaborative environment and inspire you to reimagine what's possible. Join us to help leading organizations unlock technology's potential and build a more sustainable, inclusive world.

Capgemini is an AI-powered partner that delivers tangible business value, envisioning and realizing the future of organizations through AI, technology, and people. With a rich heritage spanning nearly 60 years, we are a responsible and diverse group of 420,000 team members across over 50 countries.

We provide end-to-end services and solutions, leveraging deep industry expertise and a robust partner ecosystem across strategy, technology, design, engineering, and business operations. In 2024, the Group reported global revenues of €22.1 billion.

Develop and enhance Generative AI applications leveraging Large Language Models (LLMs) and advanced AI frameworks. Build and optimize Retrieval-Augmented Generation (RAG) pipelines, vector search mechanisms, and AI-powered workflows.

Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA. Develop REST APIs and seamlessly integrate AI capabilities into enterprise applications.

Deploy, monitor, and maintain AI solutions within cloud and containerized environments. Uphold code quality through rigorous testing, debugging, comprehensive documentation, and code reviews. Adhere to Responsible AI, security, and data governance best practices.

Demonstrate strong proficiency in Python, Object-Oriented Programming (OOP), API development, debugging, and software development best practices. Possess a good understanding of Data Structures & Algorithms, complexity analysis, and effective problem-solving.

Gain hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings. Utilize frameworks like LangChain, LangGraph, LlamaIndex, or Hugging Face.

Showcase knowledge of vector databases, semantic/hybrid search, and retrieval architectures. Experience with PyTorch, TensorFlow, or Keras is essential. Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP) is required. A foundational understanding of AI governance, data privacy, and Responsible AI principles is expected.