Senior SDET

Location: Noida, India

Department: QA

Experience: 7-9 Years

• Design, develop, and maintain automated test frameworks for AI-driven and data-intensive applications
• Validate AI/ML models, including:
• Input data quality
• Model outputs
• Accuracy, consistency, bias, and edge cases
• Perform functional, integration, regression, system, and end-to-end testing for AI tools used in medical workflows
• Collaborate with Data Scientists, ML Engineers, Developers, and Product teams to define test strategies for AI features
• Test model retraining cycles, versioning, and backward compatibility
• Ensure compliance with healthcare regulations and standards (HIPAA, FDA guidelines, HL7, FHIR – as applicable)
• Implement API, backend, and UI automation testing
• Perform data validation testing for large datasets and pipelines
• Conduct performance, scalability, security, and reliability testing for AI systems
• Participate in code reviews, test planning, defect triaging, and CI/CD pipeline integration
• Provide mentorship and guidance to junior QA/SDET team members

• 5+ years of experience as an SDET / QA Automation Engineer
• Strong hands-on experience in test automation using tools such as:
• Selenium, Cypress, Playwright, or similar
• Proficiency in at least one programming language:
• Python, Java, or JavaScript/TypeScript
• Solid experience in testing AI/ML-based applications, including:
• Model validation
• Data-driven testing
• Explainability and accuracy checks
• Experience testing RESTful APIs (Postman, RestAssured, etc.)
• Strong understanding of software testing fundamentals and QA best practices
• Experience with CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI, etc.)
• Hands-on experience with test data management and data validation
• Excellent analytical and problem-solving skills
• Strong communication skills for working with global and cross-functional teams

• Experience in medical / healthcare domain projects
• Familiarity with AI/ML concepts (model training, inference, drift, bias)
• Knowledge of healthcare data standards such as HL7, FHIR, DICOM
• Experience testing LLM-based tools, NLP, computer vision, or decision-support systems
• Exposure to cloud platforms (AWS, Azure, or GCP)
• Understanding of regulatory and compliance testing in healthcare products