Our client is seeking a highly motivated and experienced Senior QA Engineer to join their team. The successful candidate will be instrumental in ensuring the quality and reliability of new software products and solutions. The role involves working alongside cross-functional teams—spanning engineering, product, and data science—to ensure that all deliverables meet functional, performance, and reliability expectations. This is an excellent opportunity for someone who thrives in fast-paced, collaborative environments focused on continuous innovation.

Roles and Responsibilities

• Develop and maintain automated test frameworks to validate product functionality and performance.

• Partner with stakeholders to define test plans, build test scenarios, and document acceptance criteria.

• Perform manual quality assurance testing—including exploratory and user acceptance testing—when automation isn’t suitable.

• Carry out performance testing to evaluate application behavior under load and recommend optimizations.

• Monitor and report on automation test results and overall testing progress.

• Validate AI-based features with a focus on fairness, accuracy, and consistent behavior.

• Maintain detailed records of issues and their resolution through the ticketing system.

• Participate in Agile/Scrum ceremonies and contribute to sprint planning with quality insights.

• Provide QA signoff and ensure readiness of product updates/releases.

• Support continuous integration and delivery efforts with CI/CD pipeline test integration.

Qualifications and Skills

• 7 years of experience in quality engineering or test automation, including time in a Senior QA/SDET role.

• Strong proficiency in C#, .NET, Python, SQL, and OOP principles.

• Hands-on experience with Postman for testing REST APIs.

• Skilled in using test automation tools such as Selenium or equivalent.

• Solid understanding of Agile or SAFe frameworks and best practices.

• Experience with Azure DevOps, including repository and pipeline configuration.
  
  

Education

• Degree in Computer Science, Engineering, or related field—or equivalent practical experience.

Nice-to-Haves

• Background in testing AI/ML-driven applications and understanding of model validation techniques.

• Familiarity with modern frontend/backend tools such as Git, Node.js, TypeScript, JavaScript, HTML/CSS.