Amazon
Senior Product Engineer, Product Engineering
$185K–$288K
Austin, TX +3 · Senior · Full-time · Posted Jun 27, 2026
- Location
- Austin, TX
Sunnyvale, CA
Redmond, WA
San Diego, CA - Experience
- 10+ years in semiconductor product engineering or foundry process operations; preferably in high-volume wireless SoC devices manufacturing.
- Education
- Bachelor's degree in Electrical/Communications Engineering, or experience working in electrical engineering field.
- Visa sponsorship
- Candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
About the job
Develops and qualifies semiconductor products for Amazon Leo satellites and ground terminals, from product bring-up and test planning through characterization and production release.
What you'll do
- Define test, characterization, and qualification plans; analyze results and confirm production readiness.
- Coordinate with design, test, packaging, foundry, and supplier teams to address risks, failures, and product issues.
- Optimize production testing, including test-time reduction using AI and ML techniques.
What they ask for
- Bachelor's degree in Electrical/Communications Engineering, or experience working in electrical engineering field.
- 10+ years in semiconductor product engineering or foundry process operations.
- Up to 20% domestic or international travel required.
Nice to have
- Master's or PhD degree in Electrical / Communications Engineering or related field.
- RF product development and characterization experience; digital and Serdes testing; supplier experience; or statistics and data analysis proficiency.
Pay
USD 185,200.00 - 250,000.00 annually (base salary); USD 213,000.00 - 287,500.00 annually (base salary); USD 185,200.00 - 250,000.00 annually (base salary); USD 185,200.00 - 250,000.00 annually (base salary)
Tools
RF-DC, FT-WS, Exensio, JMP, FIB, SEM, IR, EMMI
AI focus
Uses AI and ML techniques, including RF-DC and FT-WS correlation and reject-oriented analysis, to reduce test time while optimizing test coverage, quality, yield, and cost.
Model-written summary · the original posting is authoritative