Paul Larsen is a production and platform engineer with 12 years of experience, currently on the Production Engineer — Platform team at Uber in Amsterdam. He blends hands-on backend systems work with platform reliability, having shaped infrastructure at Qarik Group and Unlikely AI and founded Believable Bots to productize conversational automation. An Imperial College MEng graduate fluent in English, French and Danish, Paul is an active open-source contributor — notably to a Go Telegram API wrapper and a modular Telegram group-management bot where he implemented memory-cached command disabling and robust trigger handling. Known as a self-starter and collaborative teammate, he pairs insatiable curiosity with pragmatic engineering to ship resilient, efficient services at scale.
13 years of coding experience
5 years of employment as a software developer
Masters of Engineering (MEng), Computing, Masters of Engineering (MEng), Computing at Imperial College London
GCSE and A-Levels, Maths, Further Maths, Physics and French, GCSE and A-Levels, Maths, Further Maths, Physics and French at Lycée Français Charles de Gaulle de Londres
Autogenerated Go wrapper for the telegram API. Inspired by the python-telegram-bot library.
Role in this project:
Back-end Developer
Contributions:12 releases, 92 reviews, 420 commits in 5 years 4 months
Contributions summary:Paul contributed to the development of a Telegram bot, specifically by working on the underlying API wrapper in Go. The commits focused on defining data structures for Telegram API objects, implementing filters for message handling, adding support for several message types such as photos, documents and locations, and integrating various Bot API methods for tasks like sending messages, setting stickers, and managing chat members. Refactoring code into packages and adding functions to handle media and other content indicates a progression of feature implementation.
Contributions:51 commits, 36 PRs, 367 pushes in 4 years 6 months
Contributions summary:Paul primarily contributed to the back-end logic and management features of the Telegram bot. Their work involved fixing bugs related to blacklist triggers and logging channels, as well as implementing a temporary mute function. They also refactored code to use memory caches for command disabling and log channel groups, enhancing the bot's efficiency. Furthermore, they added support for smart quotes and URL-based triggers, refining note functionality.
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