Amazon Innovation Center (Shenzhen) Company Limited
Systems, Quality, Security Engineering, Hardware Development, alexa and amazon devices
QualityEngineeringMgr
Neural analysis suggests this role is
optimal for Manager candidates.
“Quality Engineering Mgr at Amazon Innovation Center (Shenzhen) Company Limited. Skills: Quality Engineering, Product quality, Root cause analysis. Ensure products designed for quality. Meet customer expectations”
Industry & Context.
Root cause analysis; Failure analysis; Anomaly detection; Predictive quality monitoring
Up to 80% travel
What They're Looking For.
Must Have
4+ years mechanical engineering, Experience with prototyping
Nice to Have
SolidWorks simulation knowledge, Ansys Finite Element knowledge, Experience in design of complex mechanical products, Experience in design of complex equipment at volume
What You'll Do.
Ensure products designed for quality
Meet customer expectations
Focus on product quality deliverables
Establish quality goals
Investigate failure analysis
Influence closed loop corrective action
Lead quality lessons learned
Prevent quality issue re-occurrence
Manage critical issues
Resolve critical high risk items
Prevent items in next generation product
Drive continuous improvement
Influence at all levels
Manage quality program deliverables
Host milestone review meetings
Ensure cross-functional alignment
Communicate quality status
Communicate quality risks
Communicate quality recommendations
Drive timely decisions
Influence cross-functional partners
Prioritize quality issues
Resolve quality issues
Train supplier quality
Manage supplier quality
Accelerate root cause identification
Leverage AI assistants
Improve team efficiency
Drive closed-loop corrective actions
Conduct quality lesson-learned sessions
Prevent issue recurrence
Guide cross-functional teams
Conduct comprehensive testing
How You'll Work.
Team & Collaboration
Cross-functional alignment; Cross-functional partners; Cross-functional teams
Communication Scope
Communicate status; Communicate risks; Communicate recommendations
Process & Methodology
Quality program management
Full Job Description
The Quality Engineering Manager (QEM) is responsible for ensuring that our products are designed for quality and continue to meet our customers’ high expectations during the life of the product. They will focus on product quality deliverables during our product launch and sustaining. The successful candidate will establish quality goals and monitor performance, investigate with the full suite of failure analysis tools, influencing root cause and subsequent closed loop corrective action. Leads quality lesson’s learned and institutes remedies to prevent re-occurrence of quality issues and possess a high sense of urgency when managing critical issues. Their responsibility will require knowledge across a broad scope of quality, from factory process controls to customer service complaint handling. Key job responsibilities Quality Engineering Manager will be responsible for identifying risks and working with the appropriate product development and sustaining engineering functions to ensure the critical and high risk items are resolved prior to shipping a product and moreover don’t make it into next generation product. In addition to the work done in the New Product Introduction (NPI) & Sustaining phases, the Sr. QEM will drive continuous improvement in all aspects of the job, be able to deal with ambiguity, and influence at all levels of the company. A day in the life - Manage quality program deliverables end-to-end, host milestone review meetings, and ensure cross-functional alignment throughout NPI and Sustaining phases - Communicate quality status, risks, and recommendations clearly to leadership, driving timely decisions to protect customer experience - Influence cross-functional partners—including design, manufacturing, and supply chain—to prioritize and resolve quality issues that impact customers - Train and manage supplier quality teams; build supplier capability to meet Amazon's quality standards - Analyze field and factory data using AI-powered tools (e.g., anom
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