Early-career Python Software Engineer in Upper Austria, focused on API integrations, document-processing systems, and applied LLM applications. I study Artificial Intelligence at Johannes Kepler University Linz.
- Python software engineering with typed, testable modules
- Backend foundations, APIs, and integration workflows
- Applied AI systems built around LLM APIs, retrieval, and structured outputs
- Tender qualification — private client project: built a modular Python pipeline for PDF, DOCX, and XLSX ingestion, OCR fallback, LLM-assisted classification and structured extraction, domain decision rules, and Excel/JSON outputs. Uses typed interfaces, pytest, Ruff, Pyright, and pre-commit.
- AI sales assistant — private collaborative project: contributed to an open, unmerged development branch covering aiogram/LangGraph routing, RAG retrieval, async RetailCRM integration, human handoff, and tests.
- scikit-llm #118 — Anthropic API support: added provider and credential integration across multiple model families, with tests; merged upstream.
- scikit-llm #124 — model constants: centralized model constants across provider modules; merged upstream.
- Transport Catalogue — Yandex.Practicum C++ course project with JSON I/O, graph routing, SVG rendering, and Protocol Buffers serialization.
- Spreadsheet — Yandex.Practicum C++ course project with formula parsing, dependency tracking, cycle detection, and recalculation caching.
- Search Server — Yandex.Practicum C++ course project with TF-IDF ranking and parallel processing using Intel TBB.
Python, typing, pytest, Ruff/Pyright, async HTTP and external APIs, SQLite, PDF/DOCX/XLSX processing, LLM APIs and LangGraph; C++17, CMake, Protocol Buffers, graph algorithms, parsing, and parallel algorithms.