
QA Engineer – AI-Powered Test Automation
Há 22 horas
Main Responsibilities
- Develop and maintain automated test suites for full-stack .NET applications using AI-assisted tools;
- Leverage AI tools (TestRigor, Mabl, GitHub Copilot, including Copilot for Test Automation, etc.) to accelerate test creation and execution;
- Implement functional, integration, regression, and performance tests to ensure application quality and scalability;
- Work alongside developers using AI-generated code to validate functionalities and ensure software quality;
- Participate in code reviews and agile ceremonies (sprints, daily stand-ups, retrospectives);
- Design and execute continuous testing strategies in CI/CD pipelines (Azure DevOps, GitHub Actions, or similar);
- Monitor test execution and analyze AI-generated results to quickly identify and resolve issues;
- Promote a "shift-left" culture to ensure quality from the start of development;
- Create scripts for load, stress, and security testing to ensure system resilience.
- Work directly with portfolio companies to drive innovation and generate real impact;
- Leverage cutting-edge AI tools to accelerate full stack development;
- Be part of a high-performance team within a long-term investment company;
- Competitive compensation package, benefits, and professional growth opportunities.
- Degree in Data Science, Computer Science, Engineering, or related fields;
- Experience in Software Quality Assurance with a focus on automation (minimum of 3 years);
- At least 6 months of hands-on experience with AI-based QA tools (e.g., TestRigor, Mabl);
- Strong knowledge of automation frameworks such as Selenium, Cypress, Playwright, among others;
- Experience creating automated tests for APIs, databases, and UI;
- Experience working in agile teams (Scrum/Kanban) and active participation in code reviews;
- Practical experience integrating tests into CI/CD pipelines;
- Problem-solving skills and ability to leverage AI to accelerate test creation and debugging;
- Fluency in English (spoken and written) for communication in a global environment.
- Knowledge of performance testing (JMeter, k6, or similar);
- Experience with security testing tools.
- Critical thinking and attention to detail;
- Proactivity in identifying and solving failures;
- Clear and collaborative communication;
- Focus on quality from the start;
- Analytical ability for interpretation;
- Adaptability to emerging AI tools.
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