Stefan

Balvanovich

• Championed the development and integration of AI technologies, leading to the creation of an AI Agents supermarket on the platform. This involved identifying suitable AI models and tools. • Elevated user experience across devices by enhancing the front end with React. • Mentored junior developers, emphasizing best practices, and fostering team growth. • Created Rocket.Chat communication interface powered by multiple LLM's. • Worked on Internal CRM System emphesized scalability, fixed bugs, using Python, JavaScript, Java

• Developed a scalable back-end system for real-time data processing, significantly improving system throughput and responsiveness. • Developed and maintained a number of microservices to analyze customer data, integrating them with external APIs for data enrichment. • Implemented a custom ORM layer to enable efficient data operations on PostgreSQL and MongoDB databases, reducing query latency by 30%. • Led the backend team, implementing containerization using Docker and orchestration using Kubernetes, improving deployment processes and system scalability

• Developed a data-driven decision-making tool for a strategic planning department using Python and SQL to analyze construction project data, resulting in a 15% reduction in project cost. • Collaborated on a cross-functional team to develop and implement a project management tool, integrating internal systems with external interfaces for seamless data exchange. • Automated critical business processes, including payroll and scheduling, using Python scripts, saving approximately 20 hours of manual work per week. • Participated in the development of an internal API for integration with third-party services, facilitating the Data exchange between company software and external vendors.

• Designed and developed a RESTful API for the dynamic pricing module, which contributed to a 23% 23% increase in customer lifetime value through personalized pricing strategies. • Automated the creation and distribution of operational reports using Python scripts, integrating with Power BI for real-time analytics. With Power BI for real-time analytics. • Led the development of a cohort analysis feature to enable targeted marketing campaigns, resulting in an increase in annual revenue of 24,000 rubles. • Optimized backend services for high availability and low latency, using caching strategies with Redis to improve performance.