Qa Jobs 2026 (Now Hiring) – Smart Auto Apply
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QA Compliance Lead
Posted 3 weeks ago
Automation Lead Java/Python, Accelq & Ai-Augmented QA
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Overview
Job Description
- A Test Lead having 6+ years of experience with various automation tools and technologies responsible for driving quality strategy, leading QA teams, and delivering scalable automation solutions using Java, Python, AccelQ, and emerging AI-assisted testing tools. This role blends hands-on automation, intelligent test optimization, and cross-functional leadership to ensure high-quality product releases.
- Define and implement test strategies across functional, regression, integration, and end-to-end testing.
- Build and maintain automation frameworks using Java/Python.
- Develop low-code automation suites in AccelQ, integrate with CI/CD, and optimize test coverage.
- Use AI-powered tools for test case generation, defect prediction, test optimization, and exploratory testing insights.
- Mentor QA engineers, conduct reviews, and enforce best practices.
- Lead root-cause analysis, and quality metrics reporting.
- Integrate automated tests into gitlab DevOps.
- Collaborate with product, development, and business teams to align on quality goals.
- Maintain test plans, automation reports, and traceability matrices.
- Strong hands-on experience with Java and/or Python.
- Expertise in AccelQ for functional and regression automation.
- Basic experience with AI-based QA tools, including:
- AI-driven test case generation
- Intelligent defect clustering
- Predictive analytics for test coverage
- AI-assisted exploratory testing
- Knowledge of Selenium, REST Assured, PyTest, or similar frameworks.
- Expertise with stubbing and mocking of the test data.
- Strong Knowledge of Page Object Model.
- Experience with build tools like Maven or Gradle.
- Experience with API testing, UI automation, and BDD (Cucumber/Behave).
- Familiarity with SQL, Gitlab, and CI/CD tools.
- Strong analytical and debugging skills.
- Experience in Agile/Scrum environments.
- Exposure to AWS cloud platforms.
- ISTQB or similar certification.
- Experience with AI-driven DevOps or MLOps testing workflows.
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