I build scalable, high-performance backend systems and
cloud-native solutions.
Iām a backend engineer passionate about building scalable, high-performance systems that combine clean architecture with cloud-native technologies. My favorite work lies at the intersection of performance, reliability, and simplicity ā creating backend solutions that are not only powerful but also thoughtfully engineered.
Currently, I'm a Senior Software Engineer specializing in Java, Kubernetes, and enterprise integration systems. I focus on developing microservices and backend infrastructures that deliver seamless performance under high load, ensuring reliability, scalability, and maintainability.
In the past, I've had the opportunity to work across a wide range of environments ā from high-load banking systems to startup projects and cloud-native solutions. I've also built internal tools for code quality automation, improving engineering workflows and enhancing development efficiency.
In my spare time, I enjoy learning new technologies, refining my personal projects, and sharpening my engineering skills. Outside of coding, Iām passionate about playing golf in the summer, hitting the slopes for skiing in the winter, and starting my mornings with a strong espresso. I'm always energized by the challenge of building faster, more reliable, and elegantly designed systems.
May 2021 ā Present | Almaty, KZ
Feb 2020 ā May 2021 | Almaty, KZ
Jun 2019 - Feb 2020 | Almaty, KZ
Aug 2017 - Jun 2019 | Almaty, KZ
Gitlab Reviewer is an automated static analysis tool for GitLab. It uses PMD to analyze Java code in merge requests and provides AI-powered recommendations with contextual suggestions for improvements. The project supports two launch modes: as a classic JVM application and as an optimized native image via GraalVM for faster startup and reduced memory consumption. It is fully containerized using Docker for easy integration into CI/CD pipelines.
Bitbucket Reviewer is an automated code analysis tool for Bitbucket Server. It works similarly to GitLab Reviewer: it analyzes changes in Pull Requests using PMD and AI recommendations, ensuring code quality. It supports running both a classic JVM application and as an optimized native image via GraalVM. The project is fully containerized using Docker for easy integration into CI/CD pipelines.
pmd-core is a Java library that simplifies the integration of PMD static code analysis by invoking the PMD CLI from Java applications. It supports the configuration of custom rulesets, suppression files, and generates Markdown-formatted output for reporting. The library is designed for projects that require embedding PMD analysis into custom workflows or automation tools without relying on Maven plugins or direct PMD library integration.