Lead QA Engineer
New
USFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- 7+ years
- Required Skills
- PythonAgileCypressJavaJavascriptJiraTestRailSelenium
Requirements
- 7+ years of experience in Quality Assurance, including leadership or senior QA engineering roles.
- Strong expertise in QA methodologies across the SDLC, including functional, regression, integration, and end-to-end testing.
- Hands-on experience testing eCommerce platforms and native mobile applications (iOS and Android).
- Strong automation experience using tools such as Selenium, Cypress, and Appium with programming languages like Java, Python, or JavaScript.
- Experience working with CI/CD pipelines and test management tools such as Jira and TestRail.
- Familiarity with AI-driven testing solutions such as self-healing automation, visual testing, or natural language test generation.
- Proven ability to design and maintain scalable automation frameworks for web and mobile applications.
- Strong leadership, communication, and stakeholder management skills with experience driving QA strategy in Agile environments.
Responsibilities
- Lead QA strategy and execution across eCommerce, mobile applications, and integrated systems within an Agile delivery environment.
- Design, develop, and maintain test plans, test cases, automation scripts, and overall QA documentation aligned with business requirements.
- Oversee functional, regression, integration, system, end-to-end, and non-functional testing across multiple concurrent projects.
- Manage defect lifecycle including logging, triage, prioritization, tracking, and resolution using tools such as Jira and TestRail.
- Develop and maintain scalable automation frameworks for web and mobile (iOS/Android) using modern testing tools and languages.
- Collaborate with cross-functional teams including Development, Product, and Project Management to ensure alignment on quality goals and release readiness.
- Mentor QA engineers and coordinate offshore or contract testing resources to ensure consistent execution and delivery.
- Drive continuous improvement by identifying risks, improving test coverage, and leveraging AI-powered testing solutions.
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