Test Automation Architect Manager (TOSCA & AI)

Test Automation Architect Manager

The Test Automation Architect Manager is a pivotal leadership role responsible for defining, architecting, and driving the test automation strategy and implementation across enterprise programs, with a strong focus on TOSCA. T

Key Responsibilities:

• Architect, design, and implement enterprise-level test automation frameworks and strategies, primarily leveraging TOSCA.
• Drive the adoption, optimization, and governance of TOSCA across various projects and teams, ensuring adherence to best practices.
• Lead the development of scalable, maintainable, and efficient automated test suites for functional, regression, API, and performance testing.
• Evaluate, select, and integrate various test automation tools and technologies, including AI-driven solutions, into the existing ecosyst

AI & GenAI Application in Testing Skills:

• Understanding how AI/ML can be applied to optimize test processes, such as intelligent test selection, defect prediction, self-healing automation, and anomaly detection.
• Familiarity with concepts like prompt engineering and RAG pipelines for potentially generating test data, test cases, or test scripts using GenAI.
• Ability to evaluate, integrate, and champion the adoption of AI-driven testing tools and platforms to improve efficiency and coverage.

Qualifications and Skills: 

• 10+ years of experience in Quality Assurance and Test Automation, with at least 3-5 years in an Architect or Lead role.
• 5+ years of hands-on experience with TOSCA Testsuite, including deep expertise in TDM, API testing, UI automation, and CI/CD integration.
• 2+ years of experience with AI/ML concepts and their application in enhancing test automation, intelligent testing, or quality engineering processes.
• Proven experience in designing and implementing end-to-end test automation strategies for complex enterprise applications.

Tools & Technologies

Must Have Tools

• TOSCA Testsuite (including TDM, API, UI automation)
• Test Management tools (e.g., Jira, Azure DevOps, ALM Octane)
• CI/CD tools (e.g., Jenkins, Azure Pipelines, GitLab CI, GitHub Actions)
• Programming languages for scripting (e.g., Python, Java, C#)
• Version Control Systems (e.g., Git)

Good To Have Tools

• Selenium, Playwright, Cypress or other open-source automation frameworks
• API testing tools (e.g., Postman, SoapUI, Karate)
• Performance testing tools (e.g., JMeter, LoadRunner)
• Cloud platforms (e.g., Azure, AWS, GCP) for test environment management
• Basic understanding of ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) for specific test automation use cases.

Nice To Have Tools

• AI-powered test data generation or intelligent test case selection tools
• Predictive analytics tools for quality insights and defect prediction
• RPA tools for broader process automation in testing
• Experience with other commercial automation tools (e.g., UFT, Worksoft)
• GenAI tools for prompt engineering in test case design or script generation (e.g., LangChain, LlamaIndex)

Preferred candidate profile