Join Capgemini Engineering, a global leader in engineering services, where we empower innovative companies to reach their full potential. We leverage digital and software technology to provide unique R&D and engineering services across diverse industries, from autonomous vehicles to life-saving robotics. This is a permanent role within our Products & Systems Engineering community, offering a dynamic career filled with opportunities for growth and daily challenges.

Capgemini is a trusted partner for global business and technology transformation, dedicated to accelerating clients' dual transition towards digital and sustainable futures. With a diverse team of 340,000 professionals across over 50 countries and a rich 55-year heritage, we enable organizations to unlock technology's value to meet their entire spectrum of business needs. Our comprehensive services span strategy, design, and engineering, driven by leading capabilities in AI, generative AI, cloud, data, extensive industry expertise, and a robust partner ecosystem.

Develop and implement full-stack solutions using React/Angular and TypeScript for frontend applications. Build robust backend services with Python, specifically leveraging FastAPI for efficient API development. Design and manage microservices architecture, ensuring scalability and maintainability. Implement and optimize cloud solutions on AWS. Integrate Generative AI (GenAI) and Large Language Models (LLMs) into applications. Utilize agent frameworks such as LangGraph, LangChain, CrewAI, and Semantic Kernel for advanced AI workflows. Implement Model Context Protocol (MCP) and Human-in-the-Loop workflows for enhanced AI system interaction. Establish and maintain comprehensive observability and monitoring systems for applications and infrastructure.

Proven experience in full-stack development, including frontend frameworks like React or Angular and proficiency in TypeScript. Strong expertise in Python development, with a focus on building APIs using FastAPI. Solid understanding and practical experience with microservices architecture. Hands-on experience with cloud platforms, particularly AWS. Familiarity with Generative AI (GenAI) and Large Language Models (LLMs) integration. Experience with agent frameworks like LangGraph, LangChain, CrewAI, or Semantic Kernel is highly desirable. Knowledge of Model Context Protocol (MCP) and Human-in-the-Loop workflows is a plus. Proficiency in implementing observability and monitoring solutions.