Sr. Software Test Automation Engineer – Playwright with TypeScript and Agentic AI

About the Role As a Senior Software Test Automation Engineer, you will design, develop, and evolve modern test automation solutions that improve software quality, engineering velocity, and test coverage. This is a highly hands-on engineering role focused on Playwright, TypeScript, API automation, CI/CD, and AI-enabled quality engineering. You will work closely with software engineers, product teams, and QE leaders to build scalable, maintainable automation and embed quality throughout the software development lifecycle. You will also explore and apply Agentic AI, LLM-based testing, AI-assisted test generation, self-healing automation, and intelligent test analysis to modernize traditional quality engineering practices. The successful candidate is a strong software engineer who understands testing deeply and can translate emerging AI capabilities into practical, reliable QE solutions. Key Responsibilities ·       Design, develop, and maintain scalable UI and API automation frameworks using Playwright and TypeScript. ·       Develop robust automated tests covering functional, regression, integration, API, and end-to-end scenarios. ·       Define and implement automation architecture, coding standards, reusable components, and testing patterns. ·       Partner with developers and product teams to establish testability, acceptance criteria, and automation strategy early in the development lifecycle. ·       Integrate automated tests into CI/CD pipelines and enable reliable, repeatable execution. ·       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…