Evgeny Kemerov is a Technical Owner and seasoned Python backend engineer with 11 years of experience building scalable, containerized microservices and automation platforms. Based in Limassol, Cyprus, he has led architecture and delivery at Semrush—designing Kubernetes/Helm deployments, event-driven HR workflows, and Celery-based background processing while ensuring observability with Prometheus and Sentry. He combines deep hands-on skills in Django/Flask, PostgreSQL, Redis, RabbitMQ and CI/CD with pragmatic migration strategies and robust testing to maintain backward compatibility across global deployments. An active open-source contributor, Evgeny founded the tiktokpy project and has implemented core bot and scraping clients, and his earlier work on Instagram automation shows a knack for integrating complex web automation with resilient back-end logic. Known for turning heterogeneous enterprise systems into unified, auditable workflows, he brings both strategic architecture and day-to-day coding chops to cross-border engineering challenges.
11 years of coding experience
9 years of employment as a software developer
Bachelor's degree, Systems Analysis and Control, Bachelor's degree, Systems Analysis and Control at Siberian Federal University
Contributions:129 commits, 30 PRs, 86 pushes in 2 years 7 months
Contributions summary:Evgeny started the project by initializing it and setting up the base structure for automated TikTok interactions. They implemented the core client and bot structures, including browser initialization using pyppeteer and the integration of the Loguru library for debugging and logging. Further contributions included the implementation of trending items functionality, extracting data from the TikTok trending page, as well as version releases of the project.
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Role in this project:
Back-end Developer
Contributions:15 releases, 389 commits, 83 PRs in 2 years 8 months
Contributions summary:Evgeny's contributions centered on modifying the back-end logic of the Instagram bot, specifically within the `instabot` library. They primarily focused on refining existing functionality related to retrieving user information and commenting on media. The user added a new script to like media by location. Furthermore, they addressed and fixed issues related to package imports and versioning.
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