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Esta oferta expiro el 13/09/2026. Ya no acepta candidaturas.
AI QA Engineer (Agentic Testing)
Applaudo
Descripcion del puesto
About the role
You will join Applaudo as an AI QA Engineer focused on transforming software quality through AI‑powered testing and intelligent automation. In this role you will combine traditional QA automation expertise with large language models and agentic workflows to accelerate testing cycles and boost engineering productivity.
Key responsibilities
- Design, develop and maintain AI‑driven testing agents for functional, regression and integration testing.
- Build AI workflows that interpret user stories and business requirements to generate automated test scenarios.
- Evaluate and refine AI‑generated test results by improving prompts and testing accuracy.
- Develop and maintain API automation using Playwright, including REST APIs, authentication flows and token management.
- Create and sustain mobile automation frameworks with WebDriverIO.
- Integrate AI‑powered testing solutions into CI/CD pipelines and document execution evidence, logs, screenshots and reports.
- Collaborate with engineering teams to continuously improve testing strategies, automation frameworks and overall software quality.
- Research emerging AI technologies that can enhance testing efficiency and productivity.
Required profile
- Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering or a related field, or equivalent professional experience.
- 4+ years of experience in QA Automation or Quality Engineering.
- Hands‑on experience implementing AI‑powered or agentic testing solutions.
- Advanced proficiency in English.
Required skills
- Playwright for API automation.
- WebDriverIO for mobile automation.
- JavaScript and TypeScript programming.
- REST API testing, authentication flows and token management.
- CI/CD pipeline integration.
- Git and modern software development practices.
- Experience with AI‑driven testing platforms such as Testim, Mabl, Katalon AI, Reflect.
- Building or configuring LLM‑based testing workflows and AI agents.
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