Evolving Product Architecture and Scaling Development Processes

• Led architectural evolution of a large-scale product using microservices, aligning with business growth and scalability needs.
• Integrated and optimised component testing processes, enabling stable CI/CD and automated release cycles.
• Reduced infrastructure and development costs through architectural review and system optimisation.
• Introduced development and service metrics across the product to improve observability and accountability.
• Actively planned and scoped technical initiatives in collaboration with product owners and multiple teams, ensuring delivery of long-term goals.

• Built a new development department from scratch, defined internal standards, and established the tech strategy.
• Oversaw in-house development that replaced vendor software with no loss of service quality.
• Successfully migrated two mission-critical systems from Oracle to PostgreSQL, significantly reducing licensing costs.
• Re-architected the company’s DWH, moving 70% of reporting to the new platform for improved flexibility and speed.

• Led the architecture and development of a Data Lakehouse platform for enterprise-scale data storage and analysis.
• Designed and launched a secure component analysis (SCA) system to scan, validate, and deliver safe software artifacts.
• Developed a custom ETL pipeline integrated with Greenplum and Airflow, enabling flexible, reliable data processing.
• Mentored three intern cohorts (Python + Go, DevOps, React) and initiated an internal R&D direction for the company.
• Participated in pre-sales and architectural evaluation of new projects, aligning tech decisions with business needs.

Managing cross-functional teams and facilitating collaboration across diverse program positions. I act as a bridge between technical AI teams and various business units ensuring seamless integration and deployment of AI solutions. I manage third-party applications to make sure AI tools work smoothly, using tools like EazyBI to make key metrics, Google Sheets Excel and specific charts for Agile teams.

Over a three-year period, we worked closely with one of Russia's largest banks to successfully establish a robust AI monitoring system. This system operates with precision to swiftly address system failures by pinpointing their root causes and making well-informed decisions. The model expanded the scope of forecasted indicators to a total of 50,000, achieving an 85% reduction in false positive alerts. It also delivered a 20% improvement in precision compared to previous methodologies.