Inductive System QA Engineer
Role summary
Seeking an Inductive System QA Engineer for a 6-month contract in Cupertino, CA. The role requires 3+ years of experience testing complex embedded systems with hardware and software components. Key responsibilities include bug hunting, regression testing, and building test automation frameworks from scratch. The ideal candidate will have a proven ability to drive issues and milestones to completion. Preferred qualifications include knowledge of inductive charging, USB/Qi/Qi2 standards, and automated hardware testing. This onsite position focuses on ensuring clear defect reporting, effective test plan management, timely result analysis, and strong communication with engineering and program management teams.
Position Name – Inductive System QA Engineer (Staff Augmentation)
Type of hiring – Subcon
Location – Cupertino, CA (Onsite)
Duration – 6 months
Job Description:
Must-haves:
- BS/MS in EE/CS or relevant experience
- 3+ Years of experience testing complex systems with multiple hardware and software components
- Expertise in bug hunting and regression testing within embedded systems
- Demonstrated experience building and maintaining test automation frameworks from the ground up
- A proven track record demonstrating the ability to drive issues and milestones
- Good written and verbal interpersonal skills, with proficiency in English
Preferred:
- Knowledge of Inductive charging, including applications and testing methodologies
- System-level insight into charging via USB and/or Qi, Qi2 standards
- Experience with test automation tools and frameworks
- Background in automated hardware testing with equipment control
Success Criteria/Definition of Done
- All defect reports are written clearly with all applicable logs, timestamps, screenshots, etc. as required.
- Test plans are published and test case execution is managed effectively.
- Test results are analyzed and reported in a timely manner.
- Clear and effective communication with engineering teams, program managers, and other QA teams.
- Risk areas are identified and defects are characterized.
