Qa Automation Testing Engineer with AI/ML & Python

Job Title:

Experience :

Location:

Education qualification:

Mandatory skill sets:

Job Position Title:

Core Technical Skills

• Programming Proficiency

  : A strong command of programming languages is essential, with

  Python

   being the top choice due to its dominance in AI and machine learning.

• Machine Learning (ML) & AI Concepts

  : Understanding ML algorithms, neural networks, and frameworks (e.g., PyTorch, TensorFlow) is crucial for developing and testing AI models.

• Data Analysis & Engineering

  : AI is data-dependent, so skills in data cleaning, manipulation, analysis, and using tools like Pandas and SQL are critical for data testing and interpreting test results.

• Test Automation Tools & Frameworks

  : Expertise in integrating AI with automation tools (e.g., Selenium, Appium) and using AI-powered testing platforms is highly valued.

• DevOps & CI/CD Integration

  : Knowledge of Agile methodologies and integrating testing into Continuous Integration/Continuous Delivery (CI/CD) pipelines ensures continuous quality and faster feedback loops. 

Specialized AI Testing Methods & Areas

• Data Testing

  : Evaluating the quality, completeness, and potential bias in the diverse datasets used to train AI models ("Garbage In Garbage Out" principle).

• Adversarial & Ethical Testing

  : Identifying vulnerabilities through unexpected inputs (adversarial testing) and ensuring fairness, transparency, and bias mitigation in AI systems.

• Model Testing

  : Specific testing of the AI models themselves for metrics such as accuracy, precision, and performance, often involving tools like MLflow.

• Generative AI & Agentic AI

  : Skills in using and testing AI agents that can autonomously generate test cases, analyze results, and self-heal test scripts with minimal human intervention.

• Predictive Analytics & Defect Prediction

  : Utilising historical data to predict potential failure points and prioritise testing efforts in high-risk areas.

Responsibilities:

Roles & Responsibilities:

• Develop test strategies and plans in accordance with QE policies, including defining and documenting test approach and coordinating and working with change and release management teams.

• Create and maintain automated test cases.

• Create and maintain performance test cases.

• Coordinate and support in the planning and execution of end-to-end QE for Functional and Integration scenarios including creating scope, project test plan, test case execution and coordinating defect assignment and resolution.

• Support managing the User Acceptance Testing (UAT) process and activities pertaining to UAT.

• Conduct performance testing for applications including development of performance test plan and test scripts, performance test execution, and analysis of results and performance test report preparation.

• Manage and conduct requirements validation testing tasks and integration testing for all applications in scope.
• Manage and conduct end-to-end Regression Test planning and execution for any changes in the in-scope applications landscape.
• Maintain, and operationalize automation opportunities to improve efficiencies in testing delivery processes in addition to supporting the Continuous Testing and delivery methodology.

• Maintain an enterprise-wide defect management process to include production incident/problem management integration with development/test defect management.

•Create and maintain QE service catalog and QE service catalog portal. • Create and update QE processes.

• Create and update QE tooling.

Required skills and qualifications.

• Deep knowledge of QE processes and tools
• Strong understanding of one or many tools from this list Rest-Assured, JMeter, Selenium, Zephyer, JIRA, Postman.

• Excellent analytical, problem-solving, and decision-making skills

• Demonstrated knowledge of testing practices, version-control procedures, and defect management processes
• Superb computer proficiency, including database management