Over time, I developed solutions that couldn't be reduced to simple patterns. I worked on web portals for news agencies, e-commerce systems with complex inventory and payment logic, internal tools for business analytics, and services that use data from various APIs – financial, crypto markets, health standards. By building systems that connect many different data sources and interfaces, I had to take care of performance, security and scalability, which further sharpened my engineering sense.

In recent years, I have focused intensively on mobile development, using Expo and React Native as the core of my architecture. I built applications that are not just extended interfaces of web solutions, but independent entities that use geolocation, offline capabilities, authentication, push notifications, camera work and many other functionalities characteristic of modern mobile products. Through developing these systems, I gained deep understanding of the entire ecosystem – from state management layers and local databases to UI performance and application distribution through stores.

Authentication and security questions hold a special place in my development. I have always built my own solutions for login systems, not satisfied with ready-made libraries, but designing authentication protocols that correspond to the specificities of each system. I built flows that support all possible user scenarios – multiple devices, automatic token renewal, protection from abuse and identity verification through complex request and response logic. These solutions are not theoretical – they are tested on real users and serve as the foundation for stable production applications.

My strongest competencies and deepest understanding are directed precisely towards broader architecture – how to design a system that can grow, that can live for years, that won't fall when the number of users increases tenfold. That sense for the "big picture" always guides me towards solutions that are not only functional, but also technically beautiful, long-term sustainable and precisely documented. One of my most important technical challenges and successes relates to solving a specific problem within my startup, which involved verification of authentic physical locations without relying on Google Places API – which is, moreover, almost completely withdrawn from open use. By combining web scraping, AI analysis, local heuristics and calling multiple public and closed sources, I created a system that enables validation of entity presence like cafes, events and spaces, without dependency on closed commercial platforms.

A special focus of my work is the contemporary application of artificial intelligence in practical software systems. Within my startup project, I developed an AI assistant that enables users a personalized experience through contextually adapted content, connecting them with events, places and points of interest based on behavior, location and interests. This system combines data analysis, semantic processing, geolocation and vector search to achieve interaction similar to real dialogue, but with deeply contextual understanding. More technically deep, my work encompasses LLM integration through APIs, as well as development of systems that use retrieval-augmented generation principles. In this context, I use embedding models, vector databases and proprietary filtering methods to enable data search based on meaning, not mere form. Solutions arising from this enable intelligent connection of users with information, as well as automation of numerous processes within the application.

I am skilled in establishing interface logic that communicates with LLMs through defined conversational flows, fallback mechanisms and evaluation of response relevance, ensuring a high degree of user satisfaction and technical control over AI behavior. Besides practical work, AI is an area where I also formally invest significant intellectual focus. During my software engineering studies, I chose elective courses oriented towards machine learning, statistical modeling and artificial intelligence, to gain deeper mathematical and theoretical understanding of this field.