We are seeking an experienced SDET Architect with strong AI-driven test automation expertise to lead the strategic evolution of enterprise test engineering initiatives. The ideal candidate will architect intelligent automation frameworks, integrate AI/ML capabilities into testing processes, and drive scalable quality engineering solutions across enterprise platforms.
Core Responsibilities:
Strategic Leadership:
Define and execute enterprise-wide automation roadmap
Architect self-healing AI-driven testing frameworks
Standardize automation practices and testing patterns across platforms
Evaluate and implement emerging AI testing tools and technologies
Mentor senior QA and automation engineering teams
Align quality engineering strategy with business and delivery goals
AI & Machine Learning Integration:
Implement LLM-based automated test generation solutions
Build predictive analytics models for defect detection
Deploy AI-powered visual testing solutions
Automate flaky test detection and remediation using machine learning
Optimize regression suites using AI-driven risk-based testing strategies
Framework & Pipeline Engineering:
Design scalable automation architectures for web, mobile, and APIs
Integrate intelligent automation into CI/CD pipelines
Develop custom automation tools and reusable testing utilities
Optimize cloud-based distributed execution environments
Ensure high maintainability, scalability, and performance of automation frameworks
Required Qualifications:
Bachelor’s degree in Computer Science or related field
8–10+ years of experience in SDET/QA automation roles
3+ years of experience integrating AI/ML into testing solutions
Expert proficiency in Python, Java, or TypeScript
Strong expertise with Selenium, Playwright, or Appium
Proven experience designing automation frameworks from scratch
Advanced experience with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI
Strong understanding of enterprise automation architecture and best practices
Preferred Skills:
Experience with AI-driven testing platforms and LLM integrations
Strong analytical and root-cause analysis capabilities
Excellent communication and stakeholder collaboration skills
Experience leading enterprise QA modernization initiatives
Ability to explain complex AI concepts to technical and non-technical audiences
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