Quality Engineering Lead - AI Tetsing, Python, Pytest

Primary Responsibilities

• Framework Test Development
  • Lead the design, development, and maintenance of scalable, reusable test automation frameworks for UI and API testing using Playwright, Python, PyTest, Requests Library, etc
  • Develop comprehensive automated test suites following Object-Oriented Programming (OOP) principles and software design patterns (Page Object Model, Data-Driven Testing)
  • Plan and execute all levels of testing: Smoke, Sanity, Functional, Integration, Regression, UAT, Security, and Usability Testing
  • Create and maintain test data strategies, test environment management, and cross-browser/cross-platform testing
  • Create and maintain test metrics, reporting, and dashboard for quality visibility
  • Perform comprehensive API testing using tools such as Insomnia, Postman, Requests Library, and Rest Assured
  • Validate API contracts, response validation, and conduct security testing and OWASP vulnerability scanning
  • Perform SQL and relational database testing, NoSQL database testing (MongoDB, DynamoDB), and message queue testing (Kafka)
  • Conduct database assertions and data validation across systems
  • Test microservices architecture and distributed system components
  • Integrate automated tests into CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, Azure Pipelines) and support continuous release validation activities
  • Monitor test execution reports, analyze failures, and facilitate rapid feedback loops
  • Collaborate on deployment strategies and production readiness assessments using Docker and containerization concepts
  • Support Infrastructure-as-Code testing (Terraform, CloudFormation)
• Quality Assurance Collaboration
  • Conduct defect triage, root cause analysis, risk assessment, and quality reporting using tools such as Jira and Azure Boards
  • Collaborate with Development, DevOps, Product, and Business teams to ensure quality throughout the SDLC
  • Establish quality gates, define acceptance criteria for releases, and support Agile/Scrum methodologies
  • Perform test strategy development and risk-based testing approach
  • Conduct test estimation and effort planning
• AI Modern Testing Innovation
  • Leverage AI-powered tools including GitHub Copilot and LLM-based solutions to enhance productivity and test coverage
  • Utilize copilot, Claude and LLMs for intelligent test generation and optimization
  • Implement Machine Learning-based test optimization and intelligent test failure analysis
  • Generate automated documentation and leverage AI for test recommendations
  • Evaluate and implement emerging testing technologies and methodologies
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications

• Bachelor's or master's degree in computer science, Engineering, or related field
• 7+ years of experience in quality engineering and test automation
• Hands-on experience with Robot Framework and Selenium
• Experience with Sauce Labs or similar cloud-based test execution platforms
• Experience with REST API testing and tools like Postman or REST-assured
• Experience with cloud platforms (Azure, AWS, GCP) and modern DevOps practices
• Experience testing Electronic Health Record (EHR) systems and clinical applications
• Experience with healthcare cloud platforms (AWS healthcare, Azure Government, GCP healthcare solutions)
• Knowledge of healthcare standards and interoperability protocols (HL7, FHIR, DICOM)
• Have experience building or integrating AI solutions, such as:
  • Automating workflows using AI APIs (e.g., OpenAI, Hugging Face, Azure AI)
  • Embedding AI into applications (e.g., chatbots, recommendation systems)
  • Leveraging AI for data analysis, testing, or code generation
• Knowledge of CI/CD tools and processes
• Knowledge of vector databases, embeddings, or RAG-based systems
• Working knowledge of various tools such as ALM, Rally etc
• Familiarity with version control systems like Git
• Familiarity with prompt engineering and using LLMs for development tasks
• Familiarity with HIPAA compliance requirements and patient data privacy regulations
• Understand and apply AI concepts relevant to their domain
• Solid understanding of SQL and experience with database testing
• Understanding of healthcare workflows and clinical processes
• Proven solid programming skills in Python
• Proven to use AI-powered tools such as GitHub Copilot, M365 Copilot, or similar to enhance productivity and code quality
• Demonstrated prompt engineering skills, including crafting effective prompts for AI tools
• Demonstrated solid analytical and problem-solving skills
• Demonstrated excellent communication and collaboration abilities