RF Quality Engineering Manager - Consumer Electronics NPI

Amazon Lab126; Bellevue (WA); On-site; USD 117,300 - 160,000; Full time

Job summary

Amazon.com Services LLC in Bellevue, WA is seeking a Hardware Quality Engineering Manager to drive quality from concept through NPI builds, establishing risk assessments and corrective actions for robust RF and antenna solutions.

You will lead cross-functional teams, apply Lean Six Sigma methods (FMEA, DOE, MSA, ANOVA), analyze data to resolve complex issues, and travel up to 30% to onsite factories.

Qualifications

• Experience with functional specs, design verification plans and tests.
• Bachelor or higher in Electrical/Mechanical Eng or related field.
• Experience managing multiple projects in a fast-paced environment.
• 5+ years of quality assurance engineering experience.
• Strong written and spoken English; data-driven problem solving.

Responsibilities

• Understand product tech and assess risk to prevent negative customer experience.
• Guide cross-functional teams in Design for Quality initiatives.
• Deliver solutions to complex problems through data analysis and forensics.
• Communicate recommended solutions to product development and executives.
• Influence stakeholders and align cross-functionally to quality policy.
• Create standards and build consensus; set milestones during NPI phases.
• Travel up to 30% to onsite factories.

Skills

Quality assurance

DMAIC

Lean Six Sigma

Statistical tools

Project management

English proficiency

Education

Bachelor's degree in Electrical or Mechanical Engineering

Master's degree (MSME/MSIE/MSEE/MSCE)

Tools

FMEA

DOE

MSA

ANOVA

Hypothesis testing

Value stream mapping

Pareto charts

Gage R&R

Cpk

Job description

Amazon.com Services LLC in Bellevue, WA is seeking a Hardware Quality Engineering Manager to drive quality from concept through NPI builds, establishing risk assessments and corrective actions for robust RF and antenna solutions.

You will lead cross-functional teams, apply Lean Six Sigma methods (FMEA, DOE, MSA, ANOVA), analyze data to resolve complex issues, and travel up to 30% to onsite factories.