Seasoned Automation Architect & Python Developer. Evolving from Enterprise RPA to Intelligent, AI-Powered Systems.
With a foundation of over 6 years in building and scaling enterprise-grade automation solutions, my core focus is now on architecting and developing the next generation of intelligent systems. I leverage my deep expertise in process optimisation (Lean) and corporate systems (RPA, SAP) to build pragmatic, high-impact solutions. My primary interests lie in NLP for data extraction, leveraging LLMs to create autonomous agents, and predictive modelling for process optimisation.
| Project | Description | Technologies |
|---|---|---|
| document-automation-rag | Document intelligence platform leveraging VLMs and RAG for automated invoice processing and semantic search. | Python, LLMs, RAG, VLMs |
| pl-constitution-ai | An implementation of RAG system to talk with the Constitution of Poland. | Python, LLMs, RAG |
| mcp-ocr-api | A fast, fully offline OCR API and MCP server optimized for edge environments without GPUs. | Python, OCR, MCP |
| dwthon-rag-llm-wiki | An implementation of Karpathy's LlmWIKI RAG system. | Python, LLMs, RAG |
| rpa-dates | A Python library to simplify and accelerate date operations. | Python, RPA |
| rpa-sap | A robust Python module for SAP GUI Scripting and RFC automation. | Python, RPA, SAP |
| Project | Description | Technologies |
|---|---|---|
| spotify-popularity-predictor | ML model predicting Spotify track popularity based on audio features using XGBoost and Random Forest. | Python, ML, XGBoost |
| lawyer-registry-scrapper | Asynchronous web scraper built with aiohttp and BeautifulSoup4, following SOLID principles. | Python, Web Scraping, MLOps |
| london-exchange-scrapper | Robust SOLID web scraper with Playwright and Robocorp for London Stock Exchange data extraction. | Python, Web Scraping, RPA |
| palmer-penguins-mlops | MLOps project demonstrating end-to-end machine learning pipeline and model management. | Python, MLOps, ML |
I view skill acquisition as a capital allocation exercise—investing time strictly into high-leverage technologies that compound in value. My current roadmap focuses on the technical debt reduction, system scalability, and enterprise-grade architecture required to transition operations toward Agentic AI, the Microsoft Power Platform and Azure cloud.
| Status | Investment Area | Architectural Focus & Implementation | Timeline |
|---|---|---|---|
| Scheduled | PL-400: Power Platform Developer | Custom connectors, ALM, and extending enterprise architecture to eliminate manual legacy processes. | Jul 2026 - Oct 2026 |
| In Progress | AI-200: Azure AI Cloud Dev | Azure OpenAI integration, cognitive services, and deploying scalable, secure AI infrastructure. | Jun 2026 - Jul 2026 |
| Active | Open-Source Infrastructure | Maintaining rpa-sap and curating AI/LLM toolkits to standardize integrations and reduce community repetition. |
Ongoing |
| Completed | Postgraduate: AI & ML Engineering | SGGW. Operationalizing ML models: PyTorch, MLOps, Docker, and Kubernetes orchestration. | Oct 2025 - Jun 2026 |
| Completed | Software 3.0: Agentic AI | DataWorkshop. Designing, testing, and deploying autonomous, multi-agent workflows. | Jan 2026 - Apr 2026 |
| Completed | Practical LLM Application | DataWorkshop. Systemizing RAG architecture, function calling, and deterministic LLM orchestration. | Sep 2025 - Oct 2025 |
| Completed | AI_devs 3 Agents | Foundational mechanics of LLMs and building reliable AI agents. | Oct 2024 - Jan 2025 |