Accountabilities

• Define and lead enterprise-level test automation strategies spanning user interface (UI), application programming interface (API), integration, performance, and data testing layers.
• Architect scalable, maintainable, and reusable automation frameworks using Java-based technologies and modern testing practices.
• Apply artificial intelligence and Large Language Models (LLMs) to quality assurance workflows, including test generation, self-healing automation, debugging, intelligent test data creation, and defect analysis.
• Establish responsible, secure, and governed adoption of AI-powered testing tools across engineering workflows.
• Design and implement automation frameworks using technologies such as Selenium and Playwright for UI testing.
• Develop and oversee API automation solutions using tools such as Postman, RestAssured, and Swagger/OpenAPI.
• Establish robust strategies for integration testing and data validation, including ETL testing for large-scale data platforms.
• Integrate automated testing into Continuous Integration and Continuous Delivery (CI/CD) pipelines using technologies such as Jenkins, GitLab CI, Docker, and Kubernetes.
• Establish and enforce quality gates within DevOps pipelines to improve release confidence and governance.
• Lead quality assurance transformation initiatives designed to improve quality maturity, automation coverage, and delivery predictability.
• Drive data quality validation strategies across enterprise data and ETL environments.
• Collaborate with Engineering, DevOps, Data Engineering, and Product teams to align quality engineering practices with broader technology and product objectives.
• Mentor QA engineers and SDETs while establishing standards, tooling, processes, and governance models.
• Evaluate emerging AI-enabled testing capabilities and determine where they can create measurable improvements across quality engineering workflows.
• Continuously assess and evolve quality engineering methodologies, automation practices, and organizational standards.
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Requirements

• Bring 10+ years of professional experience in test automation and quality engineering.
• Demonstrate proven experience operating at an Architect or Principal level within quality engineering or software testing.
• Possess hands-on experience applying artificial intelligence to Quality Assurance (QA), including AI-assisted automation with Playwright or Selenium.
• Have practical experience using AI-assisted development and testing technologies such as GitHub Copilot, Large Language Models (LLMs), or comparable solutions.
• Demonstrate strong programming expertise, preferably within the Java ecosystem.
• Possess extensive experience building and maintaining automation frameworks for UI, API, integration, and data testing.
• Have strong experience with Selenium and/or Playwright for UI automation.
• Demonstrate experience with Postman, RestAssured, and Swagger/OpenAPI for API testing.
• Have experience with data validation and Extract, Transform, Load (ETL) testing.
• Demonstrate extensive experience integrating automated testing into CI/CD pipelines using Jenkins, GitLab CI, Docker, and Kubernetes.
• Possess a deep understanding of DevOps practices, software delivery processes, and release governance.
• Have experience defining and executing QA strategies for enterprise-scale technology platforms.
• Demonstrate strong communication, presentation, collaboration, and stakeholder management skills.
• Be capable of influencing technical and business stakeholders while driving quality engineering transformation initiatives.
• Demonstrate advanced written and verbal English proficiency.
• Bring a continuous-learning mindset and the ability to evaluate new technologies and methodologies in a rapidly evolving AI and software engineering environment.
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