Summary:
We are seeking an
AI QA Test Automation Engineer
to design, develop, and implement intelligent, AI‑driven test automation solutions leveraging
AI/ML and GenAI technologies
such as
Microsoft Copilot
and
GitHub Copilot.
The role focuses on improving software quality, accelerating test cycles, and enabling predictive and self-healing testing within a CI/CD ecosystem by leveraging
Playwright
frameworks.
Required Skills & Qualifications:
5+
years in QA / Test Automation
Strong hands‑on experience with
Playwright
Experience with various design patterns and frameworks
Experience in API automation (
Playwright /REST Assured / Postman
)
Familiarity with CI/CD tools (Azure DevOps, Jenkins, GitHub, etc.)
Strong understanding of SDLC, STLC, and Agile methodologies
Experience in cross‑browser and cross‑device testing
Knowledge of defect lifecycle and test reporting
Proficiency in Visual Studio Code (
VS Code
)
Programming skills:
Python / Type Script/JavaScript
Leverage
Microsoft Copilot
and
GitHub Copilot
for:
Accelerating
test case design and documentation
Generating
automation scripts and reusable components
Writing and optimizing
test code and utilities
Implement
GenAI-based solutions
for:
Requirement → Test case generation
Automation script scaffolding
Test data generation
Apply
ML techniques
for:
Risk-based test prioritization
Intelligent test selection
Defect prediction & failure analysis
AI-assisted
QA tools
Hands-on experience or strong exposure to:
Microsoft
Copilot
/
GitHub Copilot
Prompt engineering
for QA use cases
AI-assisted
code and test generation
CI/CD tools: Azure DevOps / Jenkins / GitHub Actions
Version control: Git/ GitHub
Cloud exposure: Azure (preferred) / AWS
Ability to drive
AI adoption in QA teams
Role & Responsibilities:
Design and develop
end‑to‑end automation test scripts and frameworks
(UI, API, and backend).
Build automation scripts using:
Playwright
AI Powered
automation tools
Analyse automation failures and ensure timely fixes for stability and reliability
Participate in regression cycles, SIT/UAT support, and production validation
Develop
self-healing automation
(dynamic locators, smart retries)
Improve automation stability using
AI-assisted debugging
Enable
smart reruns and flaky test detection
Define and implement
AI-driven QA strategies
Optimize
test coverage and execution efficiency
Analyze test and defect data using
AI/ML models
Work closely with
Product, Development, and DevOps teams
Drive adoption of
AI-powered QA practices across teams
Basic Qualifications:
BS degree in Computer Science or related discipline or
5+
years of experience as a QA resource working on multiple projects
4+
years in QA / Test Automation
1+
years in
AI-Powered QA
