Vladyslav – Golang, CI/CD, DevOps

An airline commerce platform designed to manage the full booking and order lifecycle, including flight reservations, payment processing, refunds, and order management. The platform relied on Go-based microservices to support core business workflows and ensure reliable communication between services. The project also included an internal AI-assisted development platform aimed at streamlining engineering workflows and improving developer productivity.

• Developed and maintained Go microservices for airline payments, refunds, and order management;
• Created and reviewed high-level and low-level designs (HLD/LLD) for new features and cross-service changes;
• Built an AI-assisted development platform with reusable skills, RAG, codebase memory, and MCP integrations.

A real-time multiplayer gaming platform designed to support interactive gameplay, combat mechanics, AI-driven game logic, and player management. The backend was built from scratch in Go, with a WebSocket-based architecture enabling real-time communication and supporting over 2,000 concurrent players. The project focused on delivering responsive gameplay and handling core game operations reliably at scale.

• Led the team and built a Go backend from scratch for a real-time multiplayer game, supporting 2,000+ concurrent players over WebSockets;
• Built gameplay, combat, AI, and player systems; optimized A* pathfinding to reduce server CPU usage by 35%;
• Added Redis caching, cutting repeated database calls by 80% and speeding up request processing;
• Automated CI/CD and managed AWS and Kubernetes infrastructure with Terraform; set up monitoring and alerts with Prometheus and Grafana;
• Designed communication between distributed services using Kafka and gRPC;
• Built authentication with JWT and OAuth, plus anti-cheat mechanisms to detect unfair play.

A recruitment SaaS platform designed to streamline candidate sourcing, search, and hiring pipeline management. The platform integrated multiple microservices to support core recruitment workflows, with a focus on data privacy, system performance, and scalability. Key areas included automated GDPR-compliant user data cleanup, asynchronous caching across more than 20 microservices, authentication, backend performance optimization, and cloud deployment on AWS.

• Implemented GDPR user data cleanup automation, processing 1,000+ records per month;
• Improved GitHub Actions workflows, cutting deployment time from 30 minutes to under 10;
• Implemented asynchronous data caching across 20+ microservices;
• Resolved a significant backend performance bottleneck;
• Added two-factor authentication with QR codes using Keycloak;
• Deployed and maintained services on AWS.

An enterprise backend platform supporting the operations of an insurance business, with a focus on reliability, performance, and maintainability. The system used a microservices architecture and event-driven communication to support business workflows. Key areas of work included SQL query optimization, backend performance improvements, code maintainability, and knowledge sharing through mentoring junior developers.

• Optimized SQL queries, reducing API response time from 500ms to 100ms;
• Structured the backend around microservices and event-driven communication;
• Refactored legacy code to improve maintainability and mentored junior developers.