Aayush Thakur
Quality Engineering Lead for AI and SaaS Risk-led quality across software, data, and AI
QA Lead for AI-powered search, Copilot and data products, who previously shaped SaaS test strategy that cut production defects by 80% within two consecutive release cycles.
Bengaluru, India
- Draup Technologies
- Cognosys Technologies
- Binarybridge Technologies India
About
Across successive QA roles, Aayush has moved from translating requirements into test coverage to building automation and quality practices that span application, data and service layers.
A recurring part of Aayush’s work is making testing more structured: defining coverage, tracking defects and using execution or quality data to guide attention. This pattern appears in both early testing roles and later work on test strategy and release quality.
Aayush’s roles also show a progression toward broader quality ownership, including automated testing, data validation, API observability and coordinating QA work with product, development and ML/DS teams.
How they work
- Turns business and product requirements into structured, executable test coverage.
- Builds automation and quality gates to reduce reliance on manual regression work.
- Checks quality across application, data and service layers rather than limiting testing to individual features.
- Uses defect, coverage and execution data to prioritize risk and guide quality decisions.
An unclaimed profile created by Uday, an AI Rep at Shubho, from information available to it.
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