Irshaad Khan

Quality Assurance Leader with 12+ years of experience delivering enterprise-scale quality engineering, test automation, and software validation across FinTech, Digital Payments, Quick Commerce, and Ecommerce platforms. Proven expertise in Quality Assurance & Technical Program Management, driving end-to-end program execution, release planning, risk management, & cross-functional collaboration in Agile environments. Hands-on experience in automation and quality engineering using Java, Selenium, API Testing, AWS, AI-assisted testing, and CI/CD practices to accelerate releases and improve product quality.

Successfully delivered large-scale payment and commerce initiatives, including UPI, Pay Later, Credit Cards, Wealth, Platform Migration, Localization, & Supply Chain solutions serving millions of customers. Strong leader with expertise in stakeholder management, team mentoring, test strategy, quality governance, and execution of multiple high-impact programs across engineering and business teams. Passionate about AI-driven Quality Engineering, leveraging intelligent automation, predictive testing, and data-driven quality practices to enhance testing efficiency and release confidence.

• Lead Quality Assurance Engineer II at Amazon | 2014-02 - Present | Bangalore: Spearhead end-to-end Quality Assurance for mission-critical FinTech and Quick Commerce platforms serving 200M+ customers across 10+ regions, ensuring seamless delivery of high-quality releases across manual and automated testing lifecycles with a 99.5%+ production release success rate.: Drive AI-powered Quality Engineering initiatives by implementing AI-assisted automation (ADAM Framework), smart regression, and CI/CD quality gates, including Change Guardian risk analysis, deployment monitor alarms with auto-rollback across 6 production waves and 3 regions, and Gatekeeper dependency validation, reducing test authoring time by 60%, escaped defects by 75%, and improving overall release quality by 40%. Develop and execute comprehensive test strategies, test plans, and test cases for complex frontend, backend, and API-based applications, translating business requirements into scalable QA deliverables while achieving 85%+ test coverage across 15+ microservices. Design and enhance automation frameworks using Java, Selenium, ADAM AI Framework, and API testing, increasing automation coverage from 45% to 80%+ and reducing regression execution time by 70% (from 6 hours to under 2 hours). Partner with Product, Engineering, and Program Management teams across 5+ cross-functional squads to ensure timely delivery of high-impact features, proactively mitigating quality risks and accelerating release readiness by 30% through shift-left testing practices.
• Lead Quality Assurance Engineer at Amazon | 2019-04 - 2021-12 | Bangalore: Led end-to-end Quality Assurance for 8 Amazon Pay product verticals including UPI, Pay Later, ICICI Credit Card, Amazon Wealth, Fixed Deposits, Flex Money, APX Migration, and Localization, covering 22 microservices, 180+ APIs, and 4 regional deployments.: Developed and maintained 450+ automated test cases across functional, integration, and regression suites, supporting three concurrent release trains with bi-weekly deployments. Executed 1,200+ test cycles annually for payment platforms processing ₹2,500Cr+ monthly transaction volume while ensuring PCI-DSS and RBI compliance. Collaborated with cross-functional engineering, product, and DevOps teams to implement shift-left testing and optimize release quality. Reduced production defect escape rate from 8.2% to 2.1% (74%), saving 120+ engineering hours per month in production hotfixes.
• Lead Quality Assurance Engineer at Amazon | 2022-01 - 2024-09 | Bangalore: Led Quality Engineering for Amazon Now (Tez), VAST, and JITTO platforms — covering 18 microservices, 75+ API endpoints, 12 event-driven workflows, and 3 database systems handling 150K+ daily orders across 40+ cities.: Managed regression suite of 380+ automated tests with 88% automation coverage, reducing manual testing effort from 96 person-hours to 28 person-hours per release (71% reduction). Validated end-to-end order lifecycle (placement → picking → packing → dispatch → delivery) with average order SLA of 2 hours, testing 45+ fulfillment scenarios per sprint. Reduced production incidents by 71%, improving platform availability from 98.6% to 99.7%. Lowered order failure rate from 3.8% to 1.2%, preventing 4,200+ daily order failures and preserving ₹1.8Cr+ monthly GMV.

• Bachelor of Computer Applications - Computer Applications | Bangalore University | 2010 - 2013