Senior Software Engineer

I develop and scale digital healthcare platforms using PHP, Laravel, and Vue.js, supporting more than 5,000 healthcare professionals. My work has helped improve diagnostic workflows by up to 50%.

I built an oncology calculator for medication dosing and monitoring, improving estimated diagnostic speed by 50%. I also improved page performance by 60–70% through Redis caching and backend optimization using Laravel, OctoberCMS, Docker, PostgreSQL, and Redis.

I developed government bidding platforms for the industrial sector using PHP, Laravel, Vue.js, MySQL, and TypeScript. These solutions streamlined company registration and bid management, improving bidding speed by 50% and reducing in-person bureaucracy.

I contributed to a platform supporting Brazil's industrial digital transformation, increasing company registrations by 20% and data collection by 50%. I also modernized a legacy application from PHP 5 to PHP 7, improving architecture, code quality, security, and website performance by 20%.

I contributed to a government platform that calculated the Vulnerability Index for citizens in Paraná. Using Java and SQL Server, I improved data models and increased assessment efficiency by 30%.

I refactored approximately 50 redundant files into a reusable filter, reducing filtering-related code by 50% and improving maintainability and performance with Java, JSF, PrimeFaces, and SQL Server. I also maintained the Nossa Gente Paraná social-benefits platform and optimized its database queries for higher demand.

I developed an event-driven food delivery system with payments, kitchen display system functionality, and delivery logistics using PHP, Laravel, Vue.js, React, MySQL, and Laravel Queues. The platform supported 38 locations in 22 cities and served hundreds of customers daily.

I implemented an AI-integrated chatbot microservice using Python, AWS Lambda, DynamoDB, and AWS SQS for scalable real-time messaging. I also maintained systems for e-commerce, education, and hospitality clients, modernizing database queries and reducing database usage by approximately 20–30% per project.