ABOUT

From prototype to series production — and now further.

I'm Christian Klaus, a freelance software engineer based in Geseke. For over 20 years I've built software for technically demanding systems on behalf of clients — not as a supplier of individual features, but across the entire product lifecycle: from the first functional prototype through series production and long-term maintenance in live operation.

My projects include control software for household appliances (including washing machines and dryers) at an international home appliance manufacturer, control systems for packaging machines with weighing units at a manufacturer of packaging and weighing technology, and door control systems for buses and trains at a manufacturer of door control systems (client names withheld at their request). Along the way I've worked across a range of technologies typical for embedded and industrial software: C, embedded C, and C++ at the control level on microcontroller platforms such as STM32, Renesas, Infineon, and Atmel, as well as single-board computers and SoCs such as Raspberry Pi, BeagleBone, and ESP32/ESP8266, Linux as the operating system foundation, Python and C# for simulations and tooling, CANBus and other protocols for inter-electronics communication, plus Git, CMake, PowerShell, and Continuous Integration in the development infrastructure, and system-level debugging with GDB and J-Link. It doesn't stop at the software layer, either: an oscilloscope, multimeter, and soldering iron are as much a part of my toolkit as bringing up the hardware itself — and teamwork follows agile Scrum practices.

EDUCATION & PRACTICAL DETAILS

Degree in computer science (engineering, University of Applied Sciences). Languages: German (native), English, and basic Spanish. Available for short-term on-site engagements (e.g., one to two weeks at the client's location).

THE STEP TOWARD AI

That depth is also the foundation for my second focus area: AI consulting. What I bring is the ability of an experienced software engineer to get up to speed in a new technical field quickly and thoroughly, to understand how things actually work, and to realistically judge what will succeed and what won't. That's precisely the ability many companies are missing when making AI decisions — and what I bring to the table.