About the role
Responsibilities:
- Build, execute, and maintain end-to-end test plans and test cases for new features and releases.
- Perform manual and automated testing, including functional, regression, integration, and API testing.
- Validate outputs from AI/ML components to ensure accuracy, consistency, and performance under real market conditions.
- Identify, log, and track issues with clear steps and collaborate with engineering for timely resolutions.
- Enhance and expand test automation frameworks using tools such as Selenium, Cypress, Playwright, or similar.
- Support data quality and integrity testing across complex data pipelines and reporting dashboards.
- Conduct performance, load, and stress tests for critical systems with high data throughput.
- Take part in sprint planning, code reviews, and QA retrospectives to continuously improve quality processes.
- Advocate for quality best practices and help embed QA into the development lifecycle.
Requirements:
- 7-10 years of hands-on QA experience in a software/product company or high-growth startup.
- Strong grounding in manual and automated testing methodologies.
- Experience testing data-intensive applications, APIs, and dashboards.
- Proficiency with test automation tools such as Selenium, Cypress, Playwright, or similar.
- Comfortable working with bug tracking and test management tools (e. g., JIRA).
- Solid understanding of SDLC and STLC.
- Excellent problem-solving skills and a passion for building reliable products.
- Clear communication skills and ability to work collaboratively in a fast-paced team.
Nice-to-Have:
- Exposure to AI/ML products or data workflows.
- Prior experience in fintech, investment platforms, or analytics tools.
- Familiarity with Python, SQL, or scripting languages for automation.
- Knowledge of CI/CD pipelines (e. g., GitHub Actions, Jenkins).