Jan Matejkov

Led the design and delivery of SwiftUI-based iOS applications integrating AI features and cloud backends. Refactored a legacy UIKit codebase into modular SwiftUI architecture using MVVM and Clean Architecture, significantly improving complexity and delivery velocity. Built reusable design-system components, expanded automated testing (unit, snapshot, integration), and optimized performance with profiling. Owned CI/CD release automation using fastlane and scripting, reducing release cycle time and incidents.

Delivered enterprise full-stack and cloud-native solutions combining modern web frontends, microservices backends, and data platforms. Implemented REST and GraphQL APIs and improved latency and performance for operational dashboards. Built distributed data processing with Spark, Kafka, and Airflow, and added ML capabilities using classic ML and deep learning to support recommendations and predictive analytics. Containerized services with Docker/Kubernetes and automated deployments with Jenkins and MLflow while improving deployment speed and availability.

Developed full-stack SaaS features and supported scalable data processing for large-scale user workloads. Worked across backend services and customer-facing web apps, building REST APIs and optimizing relational and NoSQL data models. Designed ETL and event-driven pipelines with Kafka and batch analytics workflows using Python, SQL, Pandas, and NumPy. Contributed to ML-driven personalization prototypes with scikit-learn and supported reliable releases using CI/CD tooling and automated tests.