Analyze automation failures, identify root causes, and improve test reliability and maintainability.
Reduce flaky tests through effective synchronization, resilient locators, test isolation, test data management, and failure diagnostics.
Develop reusable automation utilities, libraries, skills, and tools that can be leveraged across teams and applications.
Apply Agentic AI and LLM capabilities to areas such as automated test generation, test case optimization and coverage analysis, AI-assisted test maintenance, self-healing or resilient automation, failure analysis and root-cause identification, test data generation, requirements-to-test traceability, intelligent regression selection, and LLM/AI application testing and evaluation.
Explore and implement AI agents, MCP-based integrations, and AI-assisted QE workflows where they provide measurable value.
Develop or contribute to evaluation strategies for AI-powered applications, including LLM response validation, hallucination detection, prompt evaluation, rubrics, golden datasets, and quality metrics.
Participate in architecture and code reviews and provide technical guidance on automation best practices.
Troubleshoot complex automation, environment, test-data, and integration issues.
Contribute to performance, reliability, and scalability testing as needed.
Monitor automation effectiveness using metrics such as coverage, execution time, stability, defect detection, and maintenance effort.
Mentor other engineers and promote modern automation and quality engineering practices.
Continuously evaluate emerging testing technologies and AI capabilities and identify opportunities to improve QE productivity and quality.
Required Qualifications
Bachelor's degree in computer science, Engineering, or a related technical field, or equivalent experience.
5+ years of software test automation or quality engineering experience, with strong hands-on engineering experience.
Strong hands-on experience with Playwright.
Strong programming experience with TypeScript and/or JavaScript.
Strong understanding of UI, API, integration, and end-to-end automation.
Experience designing or contributing to test automation frameworks and architecture.
Strong understanding of software development practices, Git, code reviews, debugging, and CI/CD.
Experience integrating automated testing into CI/CD pipelines such as GitHub Actions, Jenkins, Azure DevOps, or GitLab.
Experience with API testing and tools/frameworks such as REST, Postman, Playwright API, or equivalent.
Strong understanding of test design techniques, test strategy, test coverage, and risk-based testing.
Demonstrated ability to troubleshoot complex automation failures and identify root causes.
Experience working in Agile/Scrum software development environments.
Strong communication and collaboration skills.
Agentic AI / AI Testing Experience
Generative AI / LLM application testing
AI-assisted software development or test automation
AI agents / Agentic AI workflows
MCP or similar agent-to-tool integration frameworks
AI-generated test cases or test scripts
LLM evaluation and testing
Prompt engineering and prompt evaluation
RAG testing and evaluation
Hallucination and factuality testing
Golden datasets and evaluation datasets
Rubric-based evaluation
AI-powered test maintenance or self-healing automation
AI-based failure analysis or test-result summarization
Experience using tools such as GitHub Copilot, Claude, ChatGPT, or other AI coding/testing assistants
Required Qualifications
Experience with Playwright using TypeScript at enterprise scale.
Experience migrating automation from Selenium to Playwright.
Experience with BDD/Gherkin and translating requirements or acceptance criteria into automated tests.
Experience with API automation and contract testing.
Experience with performance/load testing tools such as JMeter, k6, or equivalent.
Experience with Docker, Kubernetes, or cloud-based test environments.
Experience with AWS, Azure, or other cloud platforms.
Experience with test management and defect tools such as Jira, Azure DevOps, qTest, or equivalent.
Experience building reusable internal automation libraries, tools, AI agents, or developer/QE skills.
Experience with RAG, embeddings, vector databases, or LLM application architectures.
Experience establishing quality metrics and automation effectiveness measures.
What Success Looks Like
Build production-quality Playwright/TypeScript automation, not simply execute or maintain existing scripts.
Increase automation coverage while reducing manual regression effort.
Build automation that is stable, maintainable, scalable, and CI/CD ready.
Reduce flaky-test rates and improve failure diagnostics.
Identify opportunities where AI/Agentic AI can eliminate repetitive QE work.
Create reusable automation components and AI-enabled capabilities that can be adopted by other QE teams.
Collaborate directly with developers to identify and prevent quality issues earlier in the SDLC.
Demonstrate measurable improvements in automation coverage, execution speed, reliability, defect detection, and QE productivity.
Key Competencies
Hands-on engineering mindset
Automation architecture
Strong coding and debugging
Problem solving
Quality engineering mindset
AI/Agentic AI curiosity and experimentation
Continuous improvement
Technical leadership
Collaboration and communication
Ability to work independently with minimal guidance
Position Emphasis
This is a hands-on Senior QE/Automation Engineering role, not primarily a test execution or test management position. The candidate should be comfortable writing production-quality TypeScript, developing Playwright automation, debugging code, designing automation architecture, and experimenting with AI-enabled QE solutions.
Our Interview Practices
To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.
Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.
