Senior QA Automation Engineer

About the Role

We are seeking an experienced QA Engineer with strong expertise in test automation and AI/ML testing to join our growing engineering team. In this role, you will drive the quality assurance process for our software products, with a particular emphasis on automating tests and ensuring the reliability, performance, and fairness of AI-driven features.

You will collaborate closely with developers, data scientists, and product teams to deliver high-quality, scalable solutions in an Agile environment. You will not only execute tests but also design automation frameworks and incorporate AI-assisted testing practices to accelerate release cycles while maintaining exceptional standards.

Responsibilities

• Design, develop, and maintain robust automated test frameworks and scripts for web, API, mobile, and AI/ML components.
• Create comprehensive test plans, strategies, and cases covering functional, regression, integration, performance, and end-to-end testing.
• Perform specialised testing for AI/ML models, including data validation, model accuracy, bias detection, drift monitoring, and adversarial testing.
• Integrate automated tests into CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions) to enable continuous testing.
• Leverage AI-driven tools and techniques to enhance test coverage and efficiency.
• Identify, document, and track defects; collaborate with development teams to resolve issues and perform root cause analysis.
• Promote best practices, contribute to improving QA processes and methodologies, and stay current with emerging QA and AI testing trends.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
• 5+ years of professional experience in software quality assurance, focused on test automation.
• Proven experience testing AI/ML systems (e.g., model validation, data pipeline testing, generative AI outputs).
• Strong programming skills in Python, Java, JavaScript, or similar for scripting automated tests.
• Hands-on expertise with automation tools and frameworks (e.g., Selenium, Cypress, Playwright, Appium, Robot Framework, pytest).
• Familiarity with AI/ML concepts (e.g., machine learning workflows, bias/fairness testing, TensorFlow/PyTorch ecosystems) and related testing tools.
• Experience with CI/CD tools, version control (Git), and issue tracking systems (Jira, Azure DevOps).
• ISTQB certification (Foundation or Advanced Level) or equivalent is a strong plus.
• Excellent analytical, problem-solving, and communication skills; ability to work in a fast-paced Agile/Scrum environment.

Preferred Skills

• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Knowledge of performance testing tools (JMeter, Locust) and API testing (Postman, REST Assured).
• Exposure to AI-powered testing tools (e.g., Testim, Mabl, Applitools) or generative AI for test case creation.
• Background in data quality assurance for ML pipelines (e.g., Great Expectations, dbt testing).

Recruitment Process

The recruitment process includes:

• A first conversation with the HR team to get to know you and introduce the project.
• A test or a practical case study related to the position.
• A role-specific interview with your future manager.
• A final meeting with top management (if needed).
• An offer if everything is approved.

On your first day, the HR team will welcome you and introduce you to the company's mission, challenges, and tools, followed by a tailored onboarding experience.