SDET Architect ( AI Focus )

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.

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.

Benefits

• Stock options.

• Remote work opportunities.

• Flexible working hours.

• Benefits that go beyond statutory requirements.

• Collaborative environment with experienced IT professionals.

• Access to mentorship and ongoing learning opportunities.

• Opportunities to develop technical expertise in AI-driven quality engineering.

• Opportunity to influence enterprise-wide testing standards, automation strategy, and quality transformation.

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