QA Automation Engineer — AI-Native (Playwright)
Summary
QA Automation Engineer building and owning scalable Playwright test automation (TypeScript/Java) for a large US banking client, including API testing, regression testing, and root-cause analysis. The role is explicitly 'AI-native': using AI coding assistants and agentic workflows for test creation, debugging, and quality engineering.
Compensation: ₹10L – ₹15L • No equity
Our client is a large banking platform based in the US. To support their application growth, we're looking for a QA Automation Engineer with 5+ years of hands-on Playwright experience to drive our test-automation strategy. You'll build and maintain robust, scalable automation and help advance our AI-native quality engineering.
What you'll do (primary responsibilities):
- Own the design and continuous improvement of scalable Playwright automation architecture — reusable fixtures, test utilities, and coding standards.
- Use AI as a force multiplier for test creation, debugging, migration, test-data generation, documentation, and failure analysis — while staying accountable for test quality and release confidence.
- Create and maintain high-quality engineering context (requirements, acceptance criteria, test strategies, coding standards, test data, reusable project guidance) so AI tools produce reliable, consistent output.
- Investigate failures to distinguish product defects, environment issues, data problems, and automation defects; drive root-cause analysis and corrective action.
- Create detailed, comprehensive, well-structured test plans and test cases; design, implement, and debug tests and define corrective actions.
- Collaborate with the development team to ensure software meets quality standards; perform thorough regression testing when bugs are resolved.
- Improve test processes, environments, and scripts; bring a practical approach to complex product testing, especially automation for regression.
- Stay up to date with new testing tools and strategies.
**You're a strong fit if… **
- You pick up new knowledge fast and go deep rather than skim.
- You're resourceful, accountable, and obsessive about detail.
- You solve problems well independently, with minimal hand-holding.
- You thrive in a fast-paced environment and can hold multiple projects at once.
- You communicate clearly with technical teammates and work closely with others to ship.
- You're AI-native — you already use AI in your daily engineering and know where it helps and where it can't be trusted.
**You're probably NOT a fit if… **
- You need constant direction, or wait for tickets and specs before acting.
- You let AI generate tests and sign off without validating intent, coverage, and reliability yourself.
- You treat QA as box-ticking rather than owning release confidence end-to-end.
**Necessary Qualifications: **
- Bachelor's degree in Computer Science or equivalent major.
- Applied knowledge of object-oriented concepts.
- Understanding of microservices.
- Basic knowledge of databases (relational/non-relational).
- Understanding of Scrum and Agile principles.
- Understanding of SDLC, STLC, and QA methodology.
**Required skills (must have applicable work experience, not solely academic): **
- 5+ years' proven experience as a QA Automation Engineer, including 5+ years of hands-on experience designing, building, and maintaining production-grade Playwright automation.
- Advanced Playwright expertise, including Playwright Test, fixtures, resilient locators, page/component objects, parallel execution, trace viewer, network mocking, cross-browser coverage, and test isolation.
- Strong experience with TypeScript or JavaScript for Playwright automation, and the ability to integrate tests with application, API, and CI/CD workflows.
- 3+ years with Java and experience with Selenium, TestNG, Cucumber, or comparable automation frameworks.
- 3+ years of API testing using Postman, Insomnia, REST-assured, or similar tools.
**AI-Native Quality Engineering Skills: **
- Demonstrated hands-on use of AI coding assistants or engineering agents (such as Kiro, Claude, GitHub Copilot, or Cursor) for test design, implementation, debugging, refactoring, test-data creation, documentation, and analysis.
- Ability to translate requirements into clear specifications, acceptance criteria, risk-based test strategies, and testable scenarios understandable to both engineers and AI tools.
- Experience with AI-assisted and agentic quality engineering, including context management, reusable project guidance/steering files, spec-driven development, and parallel work in isolated branches or environments.
- Strong judgment when reviewing AI-generated tests: validate test intent, assertions, critical-path coverage, maintainability, data handling, duplicate coverage, flaky behavior, and false confidence.
**Preferred Skills: **
- Experience using AI to generate or migrate automated tests, including validating generated tests against requirements and maintaining traceability from requirements to test coverage.
- Familiarity with AI output evaluation, observability, structured validation, and bounded agentic workflows with human review and escalation.
- Proficiency in root-cause analysis and the ability to propose viable solutions.
- Working knowledge of Azure/AWS, Active Directory, web server (IIS), SQL, and API.
- Effective communication skills; excellent attention to detail; analytical, problem-solving aptitude.
- Ability to work independently and as a team; self-starter.
Skills
- Acceptance Criteria
- Active Directory
- Agentic AI
- Agile
- AI
- API
- API Testing
- Automation
- AWS
- Azure
- CI/CD
- Corrective Action
- Cucumber
- GitHub
- Github Copilot
- Iis
- Java
- JavaScript
- Microservices
- Observability
- Playwright
- Postman
- REST Assured
- Root Cause Analysis
- Scrum
- SDLC
- Selenium
- SQL
- Test Automation
- TestNG
- TypeScript
