Description
You lead QA strategy and execution for AI/ML, data-driven, and enterprise applications across multiple concurrent projects.
Responsibilities
- Define and implement QA strategies for AI/ML systems, including model validation, data quality checks, and continuous testing.
- Oversee manual, automation, API, and AI-focused testing covering functional, regression, performance, scalability, and integration.
- Drive test automation and intelligent testing initiatives for ML pipelines, APIs, and cloud-native services.
- Establish quality frameworks for model accuracy, bias detection, data drift, and reliability in AI-powered applications.
- Manage QA resource planning, mentoring, performance management, and career development for the team.
Required Skills
- 8+ years of experience in Software Quality Assurance, with 3+ years in a QA Lead or Test Manager role.
- Hands-on experience with Selenium, TestNG, JUnit, Postman, and JMeter or similar tools.
- Exposure to testing AI/ML systems, including data validation, model testing, and performance evaluation.
- Solid knowledge of CI/CD pipelines, Git, and DevOps-driven quality practices.
- Experience testing cloud-based applications on AWS and/or Azure.
- Strong understanding of QA methodologies, SDLC, Agile/Scrum, and defect management.
- Experience leading QA teams across multiple, complex projects in fast-paced environments.
- Bachelor’s degree in Computer Science, Engineering, or a related discipline.
Preferred Skills
- Experience with ML pipelines is a strong plus.
- Excellent leadership, communication, stakeholder management, and decision-making skills.