AI Quality Automation Engineer

This is a fully remote position, open to applicants in Latin America.

📋 Description

• Lead the advancement of quality assurance practices by developing automated solutions.

• Foster a culture of quality within development teams.

• Optimize processes using modern technologies.

• Design and maintain scalable, reusable automation frameworks aligned with product architecture.

• Create automation solutions that enhance coverage and reduce manual efforts.

• Promote quality practices within development teams, encouraging the integration of testing from early stages of the development cycle.

• Actively participate in continuous improvement processes related to testing, automation, and DevOps.

• Integrate new tools, methodologies, and capabilities based on artificial intelligence to optimize quality assurance processes.

⛳️ Requirements

• Minimum of 3 years of experience in software development.

• At least 2 years of proven experience in software testing automation.

• Minimum educational background: Bachelor's degree in Systems Engineering, Software Engineering, or a related field.

• Solid knowledge of quality assurance methodologies and best practices.

• Intermediate English proficiency for reading and understanding technical documentation.

• Experience in designing and executing automated integration, unit, and end-to-end tests.

• Proficiency in automation tools such as Playwright, Cypress, and Selenium.

• Experience using testing frameworks like Jest, Mocha, NUnit, and xUnit.

• Testing of APIs and microservices-based architectures.

• Design quality strategies based on principles such as Test Pyramid and Shift-Left Testing.

• Integration of automated tests into CI/CD processes.

• Programming skills in JavaScript, TypeScript, Node.js, or .NET.

• Demonstrable experience or interest in AI tools related to the testing lifecycle.

• Assisted generation of test cases.

• Intelligent automation of validation processes.

• Optimization and maintenance of test suites through AI.

• Practical knowledge of Microsoft Azure: App Services, Static Web Apps, Storage Services.

• Experience in microservices-based environments.

• Proficient in container management using Docker.

• Knowledge of Kubernetes.

• Participation in continuous integration and deployment pipelines for frontend and backend applications.

• Implementation of structured logging.

• Monitoring applications and tracking errors.

• Investigation and analysis of incidents in production environments.

• Contribution to continuous improvement processes focused on reliability and stability.

🏝️ Benefits

• Job stability

• Work flexibility

• Opportunity to collaborate on innovative projects within dynamic technological environments