We are looking for a skilled AI-Enabled Playwright Automation Engineer with strong experience in test automation, Playwright, JavaScript/TypeScript, and modern AI-driven QA practices. The ideal candidate should be hands-on in building scalable automation frameworks and should have working knowledge of Agentic AI, Playwright MCP, LLM-based test generation, AI agents, and prompt engineering.
The role involves designing automation frameworks, creating intelligent QA agents, integrating AI into testing workflows, and improving overall QA productivity through automation, AI-assisted development, and reusable testing ecosystems.
Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.Responsibilities:
- Design, develop, and maintain automation frameworks using Playwright, JavaScript/TypeScript, BDD, and Page Object Model.
- Build reusable automation utilities for browser handling, test data, API integration, screenshots, logging, reporting, and CI/CD execution.
- Integrate LLMs and Agentic AI workflows into QA processes for faster test case generation, script creation, analysis, and reporting.
- Work with Playwright MCP to enable AI agents to interact with browser sessions, inspect web applications, understand DOM structure, and generate automation flows.
- Create custom QA agents for test scenario generation, locator identification, Playwright script generation, defect analysis, failure debugging, and regression impact analysis.
- Use prompt engineering techniques to generate reliable test cases, BDD scenarios, automation scripts, reusable functions, and framework-aligned code.
- Apply AI-assisted development and vibe coding practices using tools such as GitHub Copilot, ChatGPT, and LLM-based coding assistants.
- Analyze automation failures using screenshots, traces, logs, failed locators, previous steps, HAR files, and execution context.
- Work on self-healing automation concepts where AI can suggest alternate locators and recommend fixes for unstable scripts.
- Integrate Playwright test suites with CI/CD pipelines for smoke, regression, and release validation.
- Collaborate with QA leads, developers, business analysts, and product teams to improve automation coverage and testing efficiency.
- Contribute to the creation of a scalable QA ecosystem combining Playwright, MCP, Agentic AI, LLMs, automation frameworks, and reporting dashboards.
Qualifications:
Required Skills
- Strong hands-on experience in Playwright automation.
- Good knowledge of JavaScript / TypeScript.
- Experience in designing automation frameworks using Page Object Model, BDD, reusable utilities, and data-driven testing.
- Good understanding of web automation concepts, locators, waits, assertions, browser contexts, traces, screenshots, and reports.
- Experience with API testing using Playwright API, Postman, or Rest Assured.
- Working knowledge of CI/CD tools such as Jenkins, GitHub Actions, Azure DevOps, or similar.
- Good understanding of Git, branching, pull requests, and code review practices.
- Ability to debug automation failures and improve script stability.
- Basic to intermediate knowledge of Generative AI, LLMs, prompt engineering, and AI-assisted testing.
AI / Agentic AI Skills
- Hands-on or working knowledge of Agentic AI for QA.
- Experience or understanding of Playwright MCP.
- Ability to create or work with AI agents for test case generation, script generation, locator analysis, execution support, and failure analysis.
- Knowledge of LLM-based tools such as ChatGPT, GitHub Copilot, Claude, Gemini, or similar.
- Understanding of prompt engineering for QA and automation use cases.
- Knowledge of RAG, vector databases, embeddings, LangChain, LangGraph, or DeepEval is an added advantage.
Nice to Have
- Experience in building AI-driven QA tools or internal automation accelerators.
- Knowledge of MCP servers, browser automation agents, or autonomous test execution workflows.
- Experience with self-healing automation, AI-based locator repair, or LLM-based failure analysis.
- Knowledge of Docker, AWS, cloud execution, or containerized test environments.
- Experience in performance testing, accessibility testing, or visual testing.
- Exposure to test management tools such as Jira, Zephyr, Xray, TestRail, or Rally.
Preferred Tools and Technologies
Automation: Playwright, Selenium, Cucumber, TestNG
Languages: JavaScript, TypeScript, Java
AI/LLM: Agentic AI, Playwright MCP, LLMs, Prompt Engineering, RAG, LangChain, LangGraph, DeepEval
DevOps: Git, Jenkins, GitHub Actions, Docker, AWS
Testing: Functional Testing, Regression Testing, API Testing, Smoke Testing, Integration Testing
Reporting: Playwright HTML Report, Allure, custom dashboards, trace viewer, logs, screenshots
