QA Automation AI

Overview

We are looking for a QA Automation Engineer with experience in Artificial Intelligence to ensure the quality of digital solutions that integrate machine learning models, advanced automation, and data pipelines. This role combines strong traditional test automation expertise with the ability to validate AI-driven systems, ensuring accuracy, stability, and reliability in high-demand environments.

Important: A strong level of English is required
, as this is a global project involving collaboration with international teams in countries such as the United Kingdom, Germany, and Japan
. While the collaboration is global,
working hours are respected according to the agreed schedule
.

• Design, develop, and maintain automated testing frameworks (UI, API, and services).
• Build comprehensive regression suites using tools such as Selenium, Playwright, Cypress, Appium
  , or similar.
• Integrate automated tests with CI/CD pipelines (Azure Dev Ops, Git Hub Actions, Jenkins, etc.).

• Design testing strategies specific to machine learning models and LLMs
  .
• Evaluate metrics such as accuracy, recall, F1-score, model drift, and robustness against variable datasets
  .
• Perform prompt-based testing to ensure reliability in conversational models.
• Validate training, inference, and data pipelines
  .

• Create detailed test cases based on acceptance criteria.
• Execute performance, load, and stress testing
  .
• Identify, document, and track defects using tools such as Jira, Azure Boards
  , or similar.

• Work closely with development, data science, MLOps, and product teams
  .
• Propose improvements in QA processes, automation strategies, and responsible AI implementation
  .
• Participate in design reviews, code reviews, and agile ceremonies (Scrum / Kanban).

• +3 years of experience in QA Automation or similar roles.
• Strong experience with at least one automation tool:
  • Selenium, Playwright, Cypress, or Appium
• Experience building test pipelines in CI/CD environments
  .
• Programming knowledge in Python, JavaScript, Type Script, or Java
  .
• Experience working with REST or Graph
  
  QL APIs
  .
• Familiarity with containers (Docker).

• Experience validating machine learning models or AI-based products
  .
• Knowledge of frameworks such as Tensor Flow, PyTorch, or Scikit-learn (conceptual or practical).
• Experience evaluating LLMs (OpenAI, Azure OpenAI, or open-source models).
• Knowledge of MLOps tools (Airflow, MLflow, Databricks, Vertex AI, etc.).
• Experience using AI-driven generative testing to increase test coverage.

• Strong analytical thinking and attention to detail
  .
• Clear communication with technical and non-technical teams
  .
• Ability to work in agile and fast-paced environments
  .
• Proactive mindset to identify risks and improvement opportunities
  .

• Degree in Computer Science, Software Engineering, Information Technology, or a related field (or equivalent practical experience).

• Accelerates time-to-market through intelligent automated testing.
• Reduces production defects through robust AI validation.
• Brings hybrid expertise across traditional QA and emerging technologies.
• Supports the implementation of responsible and trustworthy AI practices
  .