Back
Mid-level QA in metro locations with common skillset and modest brand leads to moderate competition.
Core QA skills transfer across industries but AI/multimodal testing requirements increase domain specificity.
Explicit 4–6 years plus mandatory AI testing and API-testing skills enforce strict screening filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own end-to-end manual and AI output validation testing for AI-based software products to ensure they meet business and architectural requirements.
Develop, execute, and maintain comprehensive test cases covering functional, regression, integration, exploratory, and system testing across AI-generated images, videos, recommendations, and workflows.
Log, track, and validate defects through closure; analyze root causes; coordinate with product management and development teams to deliver stable enterprise software.
4-6 years of relevant experience in QA with hands-on Agile team experience.
Proficiency in manual testing of AI-powered applications including image and video outputs, plus expertise in functional, regression, integration, and system testing.
Experience with API testing and familiarity with tools like JIRA and Git.
Strong testing skills around Generative AI concepts such as prompt testing, hallucination detection, and output quality assessment.
Experienced in testing AI-powered software involving multimodal outputs (images, videos, text) with a deep understanding of AI testing challenges and quality metrics.
Capable of test process implementation and defect lifecycle management in Agile environments, providing detailed defect reports to senior stakeholders.
Comfortable working with AI testing frameworks, cloud platforms (preferably Azure), and advanced testing techniques including bias testing, content safety, and performance/load testing.