QA Engineer - AI-Driven Customer Service

Amazon Inc.

Dallas (TX)

On-site

USD 114,000 - 160,000

Full time

3 days ago
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Job summary

Amazon Customer Service is seeking a Quality Assurance Engineer to own the QA strategy for AI-native systems that span multiple channels and scale massively. You will collaborate with Product Managers, SDETs, and SDEs to design test plans, implement automated suites, and lead cross-functional QA efforts across geographies.

You will define test strategies, ensure testability in design, and report quality metrics to stakeholders while leveraging Gen AI and best practices in quality assurance.

Qualifications

  • 4+ years of quality assurance engineering experience
  • Experience in automation testing
  • Experience in manual testing
  • Experience as QA lead on medium to large sized projects

Responsibilities

  • Work with product managers, review BRDs and analyze system designs to develop comprehensive test strategies and test plans
  • Design, develop, and maintain automated test suites using black-box and white-box testing techniques
  • Lead manual QA efforts and coordinate testing with cross-functional teams across geographies
  • Find, isolate, document, regress and track bugs through resolution
  • Debug complex issues using logs, monitoring tools, and service internals
  • Define scope and deliverables on manual and automation projects, driving execution end-to-end
  • Develop and track quality metrics to drive continuous improvement

Skills

Quality assurance
Automation testing
Manual testing
QA lead

Tools

Selenium
Appium

Job description

Amazon Customer Service is seeking a Quality Assurance Engineer to own the QA strategy for AI-native systems that span multiple channels and scale massively. You will collaborate with Product Managers, SDETs, and SDEs to design test plans, implement automated suites, and lead cross-functional QA efforts across geographies.

You will define test strategies, ensure testability in design, and report quality metrics to stakeholders while leveraging Gen AI and best practices in quality assurance.

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