Anatolii Python is an AI engineer based in Paris with 7 years of software experience and 5 years focused on Agentic AI, LLMs, RAG architectures and production-grade NLP systems. He has designed GDPR-compliant, EU-localized agentic chatbots and multi-step agent pipelines that cut time-to-market from days to hours and reduced critical incidents by 85%, demonstrating strong delivery impact in regulated fintech. His background includes production Python work across startups and scale-ups (iBanFirst, foodora) and hands-on LLMOps/CI-CD practices using tools like LangSmith and Whisper. A PhD student in mathematics who contributes to the prominent Lean mathlib projects, he brings formal-methods rigor to engineering complex ML systems, bridging research-grade proof work with pragmatic deployment.
7 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Altai State Technical University
École Polytechnique
Master's degree, Natural Language Processing, Master's degree, Natural Language Processing at Université Paris Cité
Lean 3's obsolete mathematical components library: please use mathlib4
Role in this project:
Backend Developer
Contributions:344 reviews, 873 commits, 183 PRs in 2 years 7 months
Contributions summary:Anatolii contributed to the `mathlib3` library, which is focused on formal mathematics and theorem proving. Their commits included proofs of mathematical concepts like the harmonic series diverging and lemmas related to analysis, and additions to the `topology` module. The user also collaborated with other developers, indicating a role in developing the mathematical core logic of this formal mathematics library.
Contributions:688 reviews, 19 commits, 121 PRs in 2 months
Contributions summary:Anatolii primarily contributes to the Lean 4 math library, `mathlib4`. Their commits focus on porting mathematical structures and theorems from Lean 3, such as `Algebra.Group.Commutator` and `Order.CompleteBooleanAlgebra`. The user also addresses porting issues related to Lean 4 syntax and semantics and integrating them into the project, improving the library's functionality.
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