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Senior, strong employer brand and niche GenAI QE specialization increase candidate density moderately.
Generative AI QE expertise and model validation needs are highly domain-specific and less transferable.
Explicit years (9–12), mandatory QE/GenAI testing skills and Python make filters strict.
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Manage teams (PODs) delivering AI-driven Quality Engineering (QE) services focused on generative AI.
Drive AI-based test design, automation, optimization and implement QE practices including model validation and test data strategies for AI.
Track and report KPIs, productivity, value realization; support client engagement and contribute to building reusable assets and accelerators.
9–12 years of experience in Quality Engineering/Testing.
Bachelor’s degree in Computer Science, Information Technology, or related field.
Experience with automation frameworks and AI-driven testing approaches.
Exposure to Generative AI tools and scripting, preferably Python.
Experienced in delivery management with strong team leadership skills within AI-led QE.
Familiar with implementing QE practices specific to AI models, including validation and testing strategies.
Capable of managing client interactions and driving productivity/value through AI-based testing solutions.