Sorry, this user experience was build for desktop screens. Please switch to a larger device.

Profile

Hi, I’m Tilman — a full-stack software engineer and product owner with +8 years of experience.

I am skilled in backend development with Java, Quarkus, and Vert.x, complemented by frontend work in React and TypeScript. I work comfortably with cloud-native setups and DevOps tools such as Kubernetes, Helm, and ArgoCD. Alongside my engineering work, I bring hands-on product management experience, shaping requirements, prioritising backlogs, and collaborating with stakeholders to translate user needs into scalable technical solutions. Beyond my core stack, I enjoy experimenting with languages like Go and Python and exploring machine learning concepts.

☄️ Projects

King of the hill chess engine

King of the Hill is a chess variant where the player wins by moving the king into one of four center fields. NextMagnus is a Java chess AI that plays exactly this variant. It allows the use different search algorithms to find the best move; utilizes bit boards for accelerated computations on CPU level; as well as caching of examined tree branches. The chess engine was created in corporation with two other students as part of a university research project.

Play a round against NextMagnus

Corral++

Corral++ is a serverless data-processing framework written in Go that allows execution of Map-Reduce queries on large amounts of data. In this experimental branch of the framework, I implemented an advanced logging system and collected data to gain deep insights into the impact of certain parameters. In the second step, I focused on an improvement of the polling process that is required to monitor the progress of the individual map and reduce function invocations. I used the collected data to build ML models that can predict the execution time of the function. These were compared with different linear polling algorithms that I implemented, in order to find the most efficient option that reduced network traffic and delays.

Check out the source code and the ML models

CardBooster

CardBooster is a learning app designed to help apprentices prepare for the IHK chef exam. The project started as a deliberately small and focused MVP for a niche audience, with more than 500 learning cards structured around the actual exam topics. I built the application end to end, covering backend development with Java and Quarkus, a React/Next.js frontend, authentication with Keycloak, and a PostgreSQL-based persistence layer. I set up and maintained the infrastructure using Docker Swarm, implemented a freemium payment model via PayPal, and gained hands-on experience with SEO and app marketing.

Check out the live application

About this page

The assets for this page were crafted and animated in Blender. The rest of the magic happens in JavaScript utilizing the three.js framework and some additional libraries such as three-nebula to add special effects.

Check out the source code.

🛸 Contact

Find me on LinkedIn

Check out my GitHub account

Send me an E-Mail