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CHANDRASHEKHAR REDDY

@chandrashekharreddy

I build AI-driven QA automation frameworks that accelerate reliable enterprise software releases.

India
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What I'm looking for

I'm looking to build scalable QA automation and AI-driven quality engineering solutions, partnering with business stakeholders to improve UAT, release readiness, and reliable software delivery.

At Crowe LLP, I build parallelized Playwright end-to-end automation frameworks for enterprise clients including SBA, IEDC, and Nucor. My work cut regression cycle time by 40% and supported 50+ releases with zero critical post-release defects.

I scale cross-browser Selenium WebDriver suites covering 10,000+ test cases across three browsers, reducing manual regression effort by 60%. I also design test cases, scenarios, and quality strategies that improve defect-detection coverage and reduce production escapes by 50%.

I partner closely with business stakeholders to plan UAT, author acceptance scripts, manage defect triage and re-testing, and secure formal sign-off before go-live.

I build AI-powered generators for test cases, scenarios, and quality strategies using Microsoft Copilot Studio and AI Studio, with human-in-the-loop verification for accuracy. I’ve also created MCP-based assistants and Power Automate workflows that reduce documentation lookup and manual QA effort.

Experience

Work history, roles, and key accomplishments

Crowe LLP logoCL
Current

QA Automation Engineer

Mar 2021 - Present (5 years 5 months)

Built parallelized E2E test automation frameworks in Playwright, cutting regression cycle time by 40% and supporting 50+ releases for enterprise clients. Planned and coordinated UAT cycles, developed AI-powered test generators, and automated QA workflows with Power Automate.

Education

Degrees, certifications, and relevant coursework

Lovely Professional University logoLU

Lovely Professional University

Bachelor of Technology, Computer Science Engineering (AI/ML)

Grade: 8.0/10 CGPA

Bachelor of Technology in Computer Science Engineering with a focus on AI/ML, achieving a CGPA of 8.0/10.

Tech stack

Software and tools used professionally

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