Senior Engineer (Python, Cloud, AI/GenAI)

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members globally in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.

• Over 5 years of experience in writing high-quality, scalable code and designing robust software architectures using libraries like Streamlit, Flask, SQLAlchemy, Celery
• Strong knowledge of Python libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and Keras, with practical experience in building AI-powered applications
• Expertise in frameworks like LangChain and hands-on experience with large language models (e.g., GPT-4, LLaMA)
• Proficient in working with embeddings, vector databases, and prompt engineering
• Proven ability to seamlessly integrate AI components with other system elements (e.g., APIs, databases) to deliver cohesive solutions
• Excellent command of English; knowledge of German is a plus
• Eager to adopt new technologies and embrace technical challenges
• Highly organized, self-reliant, and passionate about sharing knowledge
• Strong communication and teamwork abilities
• Dedicated to building and contributing to a Center of Excellence for AI development, driving innovation and promoting best practices across the organization

• Design and develop scalable back-end solutions using Python in cloud environments
• Contribute to solution architectures across Python, cloud and Java-based systems
• Act as a technical consultant or lead in Python development projects
• Support AI and GenAI initiatives, including LLM-based solutions
• Promote clean code, best practices, and high engineering standards
• Mentor team members and share technical knowledge through workshops