Quality Assurance Lead - Manual/Automation Testing

As an experienced QA Lead, your role will involve driving the quality strategy for AI/ML-based software products. You will be responsible for defining, implementing, and owning the QA strategy and processes for product releases. Your leadership skills will be crucial in mentoring a team of QA engineers and ensuring best practices in manual and automation testing. Collaborating with Product, Development, and Data Science teams will be essential to ensure quality across AI/ML models and web-based applications. Key Responsibilities: - Define, implement, and own the QA strategy and processes for AI/ML product releases. - Lead and mentor a team of QA engineers, ensuring best practices in manual and automation testing. - Design, develop, and maintain automation test frameworks (Selenium, PyTest, or similar). - Perform API testing (REST / SOAP / GraphQL) using tools like Postman, Rest Assured, or equivalent. - Validate data pipelines, transformations, and storage with strong database testing (SQL / NoSQL) skills. - Oversee test planning, execution, defect tracking, and reporting. - Ensure product quality in Linux-based environments and across multiple platforms. - Drive continuous improvement in test coverage, automation, and QA processes. Qualifications Required: - Bachelor's/Master's in Computer Science, Engineering, or a related field. - 8- 12 years of QA experience, with at least 2+ years in a lead/mentorship role. - Strong background in manual testing and test automation. - Hands-on experience with Selenium, TestNG, JUnit, or similar frameworks. - Solid knowledge of API testing tools (Postman, Rest Assured, etc.). - Proficiency in SQL / NoSQL databases for data validation. - Familiarity with AI/ML product testing (model accuracy, performance, and integration) is a strong plus. - Exposure to Linux/Unix environments. - Strong problem-solving skills, attention to detail, and effective communication. Good to Have: - Knowledge of CI/CD tools (Jenkins, GitLab CI, etc.). - Experience with cloud platforms (AWS, GCP, Azure). - Understanding of performance testing and security testing. - Prior experience in a product-based company. As an experienced QA Lead, your role will involve driving the quality strategy for AI/ML-based software products. You will be responsible for defining, implementing, and owning the QA strategy and processes for product releases. Your leadership skills will be crucial in mentoring a team of QA engineers and ensuring best practices in manual and automation testing. Collaborating with Product, Development, and Data Science teams will be essential to ensure quality across AI/ML models and web-based applications. Key Responsibilities: - Define, implement, and own the QA strategy and processes for AI/ML product releases. - Lead and mentor a team of QA engineers, ensuring best practices in manual and automation testing. - Design, develop, and maintain automation test frameworks (Selenium, PyTest, or similar). - Perform API testing (REST / SOAP / GraphQL) using tools like Postman, Rest Assured, or equivalent. - Validate data pipelines, transformations, and storage with strong database testing (SQL / NoSQL) skills. - Oversee test planning, execution, defect tracking, and reporting. - Ensure product quality in Linux-based environments and across multiple platforms. - Drive continuous improvement in test coverage, automation, and QA processes. Qualifications Required: - Bachelor's/Master's in Computer Science, Engineering, or a related field. - 8- 12 years of QA experience, with at least 2+ years in a lead/mentorship role. - Strong background in manual testing and test automation. - Hands-on experience with Selenium, TestNG, JUnit, or similar frameworks. - Solid knowledge of API testing tools (Postman, Rest Assured, etc.). - Proficiency in SQL / NoSQL databases for data validation. - Familiarity with AI/ML product testing (model accuracy, performance, and integration) is a strong plus. - Exposure to Linux/Unix environments. - Strong problem-solving skills, attention to detail, and effective communication. Good to Have: - Knowledge of CI/CD tools (Jenkins, GitLab CI, etc.). - Experience with cloud platforms (AWS, GCP, Azure). - Understanding of performance testing and security testing. - Prior experience in a product-based company.