Lennart Paul

I’m Lennart Paul, a Business Informatics graduate currently pursuing my M.Sc. in Information System Management at Universidade Nova de Lisboa. During my studies and internships at Landesbank Baden-Württemberg and the University of Sevilla, I gained practical experience in software engineering, AI research, and product ownership. I’m particularly interested in the intersection of technology and business — especially in areas like machine learning, full-stack development, and the testing of generative AI systems. Outside of work, I enjoy analyzing ETFs, cooking healthy meals, and playing tennis

I have gained diverse professional experience in the areas of software development, AI research, and IT product management. At Landesbank Baden-Württemberg (LBBW), I worked as a Software Engineering Intern and later as a Bachelor student, developing full-stack applications in Next.js, implementing backend authentication in Java, and designing quality assurance processes for AI tools. During my research internship at the University of Sevilla, I configured and deployed machine learning algorithms on cloud servers and contributed to scientific documentation on AI for cancer recognition. Additionally, I supported Footprint Technologies in recruiting machine learning specialists, broadening my understanding of the tech industry from a people and process perspective.

Bachelor Thesis – LBBW (2024–2025):
Research on testing of generative AI; full-stack development in Next.js; led QA and acceptance testing for internal AI tools.

Research Assistant Internship – University of Sevilla (2024):
Configured and deployed ML algorithms on cloud servers; conducted academic research and documentation for cancer recognition systems.

Software Engineering Internship – LBBW (2023–2024):
Implemented authentication in Java backend; developed frontend features in Angular; set up CI/CD deployment pipelines.

IT Product Owner (Working Student) – LBBW (2022–2023):
Designed process to evaluate software quality across releases; maintained and improved technical documentation.

Technical Recruiting – Footprint Technologies (2021–2022):
Sourced and evaluated machine learning engineers; supported recruitment for AI-driven product development.