I am a Site Reliability Engineer at Red Hat and a product architect focused on building resilient, automated infrastructure for high impact, real world systems. My work lives at the intersection of network engineering, observability, and applied machine learning, where I design platforms that move beyond passive monitoring toward adaptive, self healing behavior. I specialize in translating low level telemetry and time series signals into actionable insight through automation, AI-assisted operations, and clear operational feedback loops.

Alongside my role at Red Hat, I have led the engineering and architectural direction of fintech platforms such as Qwiva and Midlr, where I oversee distributed teams and take responsibility for the security, reliability, and autonomy of web-client and POS hardware integrations. I regularly bridge deep, hands on engineering spanning network and server automation, containerized microservices, and observability stacks with the strategic leadership required to scale products from early beta to production environments.

I am currently based in the Czech Republic and pursuing a master’s degree in Communication and Networking Technology, where my academic research centers on anomaly detection in optical fiber networks. This work applies signal processing and machine learning techniques to identify subtle disturbances and potential security threats in polarization and acoustic sensing data, reinforcing my broader interest in reliable, intelligent infrastructure. As a speaker, I aim to share practical lessons from operating systems at scale while offering a forward-looking view on how AI-driven operations and anomaly detection are reshaping network reliability and modern infrastructure.