Paul Larsen is a production-focused platform engineer with 13 years of experience building reliable backend systems across startups and large tech companies, now working at Uber and founder of Believable Bots. An Imperial College MEng graduate fluent in English, French and Danish, he blends hands-on systems engineering with product-minded ownership from roles at Improbable, Unlikely AI and Qarik Group. He contributes to open-source tooling for chat automation—authoring Go-based Telegram API wrappers and modular group-management bots—demonstrating pragmatic API design and cache-aware refactors. Known for curiosity and self-starting energy, he pairs deep technical craft with proactive teamwork to ship resilient platform features at scale.
13 years of coding experience
5 years of employment as a software developer
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
Masters of Engineering (MEng) Computing, Masters of Engineering (MEng) Computing at Imperial College London
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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