Gabriel Afonso Leal

Provided quality assurance for Intelex's V6 EHSQ platform, designing and maintaining automated integration, regression, and E2E suites. Built API test automation in Python and a BDD framework with Robot Framework and Selenium, and validated event-driven data propagation across microservices.

• Provide quality assurance for Alliance, a module of Intelex's V6 EHSQ platform — C# microservices on Microsoft Service Fabric with a JavaScript front end — designing and maintaining automated integration, regression, and E2E suites that validate service-to-service communication and business-critical flows, prioritized through risk-based testing and the test pyramid.
• Built comprehensive API

• Implemented automated acceptance and E2E tests in C# (NUnit, Selenium) for banking-critical software, increasing test coverage by nearly 60% while keeping flakiness below 10%; adapted an existing manual test plan to automation in close collaboration with manual testers for maximum impact and a smooth transition.
• Built API contract and stress tests with Postman and JMeter — automated within

• Designed and implemented a BDD automation framework using Java, Cucumber (Gherkin), and Selenium on the Page Object Model (POM) pattern, with custom lifecycle hooks, WebDriverManager for automated driver management, and cross-browser execution — enabling plain-text feature files and a more collaborative team workflow.
• Developed support libraries for logging, error handling, and warnings (Ja

• Participated in the development of Spectrum Power 7's electrical calculation system — a Fortran core invoked through C, C++, and Java layers, exposed via a Python REST API (Flask) on a Siemens-proprietary web server — validating calculation accuracy against known-correct reference values from masked real client data, with exact-match precision required for critical software.
• Drove a shift-

During a university robotic trekking competition, I developed the computer vision system for an autonomous robot using Python, OpenCV, and PyTorch. I built and optimized a CNN for real-time terrain classification and obstacle detection, enabling the robot to navigate complex, uneven paths autonomously. The system achieved over 92% accuracy on embedded hardware (Raspberry Pi), and the robot success

With experience in Python-based automation frameworks and a background in quality engineering, I have practical skills relevant to Robotic Process Automation (RPA). I have developed automated test scripts using UiPath to simulate user interactions and validate system workflows — a foundation that translates directly to designing RPA bots for repetitive UI-based tasks. My experience with CI/CD pipe

Pursued a degree in Computer Engineering, focusing on software development and quality assurance.