Senior Backend Developer focused on PHP, Laravel, API architecture, integrations, and production performance.

I build backend systems that are practical to operate: clear domain boundaries, reliable integrations, queues for async work, measurable performance improvements, and enough tests to keep production changes calm.

Backend: PHP 8.x, Laravel, Eloquent ORM, REST API, MVC, SOLID, Composer
Data: PostgreSQL, MySQL, MongoDB, Redis, query optimization, indexing
Architecture: service decomposition, event-driven flows, queues, webhooks, legacy refactoring
Integrations: Telegram Bot API, OpenAI API, Anthropic API, payment and internal APIs
Infrastructure: Docker, Linux/shared hosting, cron jobs, backups, monitoring basics
Frontend touchpoints: JavaScript, HTML, CSS, Vite/Webpack, Core Web Vitals optimization
Quality: Git, code review, API documentation, Postman, Swagger/OpenAPI, Pest/PHPUnit basics

• Designed and maintained Laravel-based web applications for a healthcare business: main clinic website, online appointment flow, payment-related platform, Telegram notifications, and AI assistant integration.
• Improved production performance, including LCP optimization from roughly 4.5s to 1.8s.
• Automated operational workflows: Telegram confirmations and AI-assisted navigation reduced manual admin work on typical requests.
• Refactored legacy Laravel codebases and optimized SQL-heavy backend paths for better maintainability and response time.

• Prefer simple architecture with explicit trade-offs over abstract complexity.
• Keep business logic readable, testable, and separated from delivery concerns where it matters.
• Use queues and async jobs when synchronous work would hurt user-facing latency.
• Optimize with data: profiling, query plans, p95 latency, Core Web Vitals, and measurable business impact.
• Treat documentation as part of delivery: setup notes, API examples, and operational context.

Backend showcase service for NBA statistics, player efficiency analysis, team summaries, and leaderboard-style JSON responses.

The project is designed to show backend decisions that are usually hidden inside commercial closed-source systems:

• domain modelling for teams, players, and stat lines;
• analytics metrics such as TS%, eFG%, per-36, and assist-to-turnover ratio;
• provider abstraction for future live sports APIs;
• CLI JSON output;
• tests and GitHub Actions example;
• architecture notes with trade-offs.

• Email: inotmustdie@gmail.com
• Telegram: @inotmustdie
• Location: Moscow region, Russia
• Preferred format: remote, full-time