IT Quality Engineer (904)
About The Position
Quality Engineer (QE) leverages both automation and AI-driven testing intelligence to elevate the QA department’s capabilities – ensuring software releases are faster, more reliable, and data-informed. This hybrid role blends engineering precision with AI innovation to set new standards for quality in modern development pipelines. As a QE, you will play a key role in ensuring the quality, reliability, and performance of software products throughout the development lifecycle. Working within the Quality Services department, this role combines traditional testing expertise with modern AI-driven tools and agents to improve efficiency, accuracy, and predictive quality analysis. The QE collaborates closely with developers, product owners, and QA analysts to automate quality processes and enable intelligent test optimization.
Requirements
- 3+ years of experience in software testing or quality engineering.
- Solid understanding of SDLC, QA methodologies, and agile practices.
- Hands-on experience with test automation tools (e.g., Selenium, Playwright, TestNG, Tosca, NeoLoad).
- Experience with CI/CD tools (Jenkins, GitHub, Azure)
- Basic familiarity with AI/ML technologies, including model integration or API-based AI services.
- Strong analytical and problem-solving skills, with attention to detail.
Nice To Haves
- Experience deploying or managing AI testing tools
- Proficiency in Java, Python, JavaScript, SQL, or similar languages used for automation and AI integration.
- Knowledge of cloud and container environments (Azure, Docker, AWS).
- Exposure to data-driven or AI-enhanced analytics dashboards.
Responsibilities
- Collaborate with cross-functional teams to define test strategies, acceptance criteria, and quality metrics aligned with business goals.
- Develop, maintain, and execute automated test scripts for functional, regression, integration, and performance testing.
- Implement and manage AI testing agents that assist with: Intelligent defect detection and root cause analysis, Dynamic test code generation based on usage patterns and data, Predictive quality analytics for release readiness, Test script maintenance and optimization using AI models.
- Integrate AI agents with CI/CD pipelines to perform continuous validation and risk-based testing.
- Leverage machine learning insights to identify recurring quality issues and propose preventive measures.
- Support manual and exploratory testing when needed, ensuring comprehensive test coverage.
- Monitor and report on test coverage, defect density, and AI agent performance metrics.
- Continuously enhance QS processes through automation, data-driven feedback, and AI tool adoption.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
