Performance Test Engineer

About the Role

We are looking for a QA Engineer with strong hands-on experience in automation, API testing, integration, and regression testing, with added exposure to AI-based platforms. You will be responsible for ensuring product quality across the software development lifecycle by designing robust test cases, developing automation frameworks, and validating AI-driven systems.

Key Responsibilities

• Design, develop, and execute automated test scripts for functional, regression, and integration testing.
• Perform API testing using tools like Postman, RestAssured, or Karate to validate endpoints, payloads, and workflows.
• Collaborate with developers and product teams to ensure continuous integration (CI/CD) quality checks are in place.
• Analyze test results, identify defects, and ensure timely resolution through proper tracking tools (e.g., JIRA).
• Contribute to automation frameworks and maintain test suites to support fast-paced development cycles.
• Conduct exploratory and regression testing to uncover edge cases.
• Work with AI/ML product components, validating model outputs, data integrity, and system behavior.
• Participate in code reviews and provide feedback on testability and quality best practices.
• Required Technical Skills
• Automation Testing: Selenium, Cypress, Playwright, or similar frameworks.
• API Testing: Postman, RestAssured, SoapUI, or Karate.
• Programming/Scripting: Proficiency in Java, Python, or JavaScript.
• Integration & Regression Testing: Strong experience in end-to-end validation of complex systems.
• CI/CD Tools: Jenkins, GitLab CI, GitHub Actions, or similar.
• Version Control: Git/GitHub/GitLab.
• Test Management: JIRA, TestRail, or equivalent.
• AI/ML Exposure: Understanding of model testing, data pipelines, or validation of AI-based features (not deep but hands-on exposure is expected).
• Good to Have
• Experience with cloud platforms (AWS, GCP, or Azure).
• Familiarity with containerization (Docker, Kubernetes).
• Knowledge of performance testing tools (JMeter, Locust).
• Awareness of AI testing challenges like bias, explainability, and model drift.

Soft Skills

Strong problem-solving and analytical skills.

Excellent communication and collaboration abilities.

Detail-oriented mindset with focus on product quality.