From CFD simulation at Audi to big data engineering at IBM — now building AI-powered workflows that turn complexity into clarity.
I started my career as a CFD simulation engineer at Audi — seven years of thermodynamic modelling and automating simulation pipelines in Győr and Ingolstadt. That obsession with automating repetitive work led me into data engineering, then into AI.
Today I build data pipelines at IBM and spend the rest of my time exploring AI automation: agent workflows, LLM tooling, and practical systems that actually hold up under real use. Based in Budapest.
Outside the terminal: compound lifts, classical piano, Stanisław Lem, cosmology, and Scandinavian design. In no particular order.
Personal brand site built from scratch in a focused sprint. Design system, copy, and layout — all developed with Claude Code.
Personal health intelligence system connecting Garmin data, blood pressure logs, and weight tracking into a unified AI-analysed dashboard.
Docker-based Claude Code sandbox with a curated set of MCP servers extending its reasoning and tool access. A reproducible AI-assisted development environment running entirely on local hardware.
Design and implement intelligent workflows using LLMs, agents, and automation platforms. Turn repetitive processes into autonomous systems.
Robust data pipelines that extract, transform, and load reliably. From Parquet files to cloud data lakes — clean, logged, maintainable.
I explore agent workflows, AI tooling, and practical automation patterns. Documenting what works, what breaks, and what earns trust in real use.
Started as a CFD simulation engineer at Audi in 2012, moved into data engineering and AI. Each career shift deliberate — driven by curiosity and a drive for deeper technical leverage.
Currently at IBM building big data pipelines, while simultaneously exploring AI automation and agent development.
Building and maintaining large-scale data pipelines in a global enterprise environment. Python, PySpark, SQL, Airflow, Jenkins. Focus on automation, robust logging, and cloud storage integration.
Data analysis of manufacturing processes and sensor measurements for automotive safety systems. Python-based data collection, ML/AI analysis, and technical impact assessment.
First professional coding role. Python fundamentals, APIs, version control, and software development foundations. The start of a deliberate career transition into engineering.
7.5 years in thermodynamic simulations for whole-car development. 8 months at Audi HQ in Ingolstadt. Designed and automated simulation pipelines — the beginning of a lifelong automation obsession.
Open to data engineering, AI automation, and consulting opportunities. Based in Budapest. Best for recruiter outreach, technical collaboration, and builder conversations.