Johan – React, Python, Microsoft Azure

Led a high-impact migration project for a food delivery platform, focusing on porting and adapting advertising technology components to a new platform. The project involved modernizing existing adtech functionality and ensuring a smooth transition to the new technical environment.

• Acted as DRI for the migration of legacy services to the new brand-shared platform;
• Discovered and fixed an incident-level bug that had been in production for years;
• Identified and documented critical data parity issues, proactively coordinated with partner teams to prevent major launch delays;
• Accelerated delivery by contributing core code and actively dismantling cross-team engineering bottlenecks.

A PWA-based web application for planning, logging, and analyzing sports training. The platform supported individual athletes, self-coached paying users, professional coaches using SaaS features, and internal coaching teams, providing tools for structured training management and performance analysis.

• Migrated 10+ years of production data to managed cloud infrastructure;
• Rapidly ported .NET MVC app to a modern TypeScript (Bun) + React stack, using an AI-assisted workflow;
• Engineered an agentic AI assistant utilizing OpenAI API and Azure AI Foundry, enabling autonomous tool execution and retrieval of proprietary business knowledge;
• Optimized cloud service usage, reducing infrastructure costs by 53%.

An in-house web application for managing sports and fitness coaching. The platform combined training management, nutrition tracking, and direct communication between coaches and clients through an integrated chat.

• Designed and provisioned a production cloud-native environment;
• Built CI/CD pipelines and observability infrastructure;
• Led an international engineering team;
• Developed backend and mobile features;
• Executed Python-based ETL for a major version upgrade.

A diagnostic medical device for reading and analyzing lateral flow tests, covering the full product lifecycle from initial design through development. The project followed IEC 62304 and ISO 13485 requirements for regulated in-vitro diagnostic solutions.

• Owned architecture across backend, frontend, and analytics;
• Designed and implemented an integrated software and hardware solution;
• Developed Python-based analytics workflows using NumPy and Pandas;
• Delivered a production-grade system under strict regulatory requirements.

Developed native Android and iOS applications integrating custom computer vision algorithms with cloud-based data visualization. The platform enabled users to process visual data and access insights through interactive visualizations.

• Built a native Android application utilizing computer vision technology with Java and the Android SDK;
• Ported the application to iOS, implementing an Objective-C++ bridging layer to enable the Swift frontend to utilize the native OpenCV C++ library;
• Developed a reliable image processing pipeline through extensive data exploration and analysis of a large image dataset;
• Implemented a cloud backend and database to collect telemetry and visualize results on an interactive world map.