Electro-Optical Test Systems Architect

Amazon Inc.; Redmond (WA); On-site; USD 117,000 - 160,000; Full time

Job summary

Amazon Leo is expanding its electro-optical test architecture team to design, build, and qualify electro-mechanical optical test stations for manufacturing-line integration and volume production of optical intersatellite link systems.

You will develop end-to-end test environments, define DVT plans, and perform optical metrology and RCA to ensure robustness, repeatability, and high first-pass yield across thermal cycling and TVAC conditions. Proficiency in Python, MATLAB, and LabVIEW is expected.

Qualifications

• Bachelor's degree in engineering, physics, or equivalent.
• 4+ years of industry experience in electro-optical or opto-mechanical systems development across full product life cycles, from concept to production.
• Experience with lasers, detectors, modulators, optical fiber and devices, testing and characterization.
• Experience with optical metrology for component and system test and qualification.
• Direct experience running thermal cycling (TC) and/or thermal vacuum (TVAC) test profiles for high-precision optical or electro-mechanical systems.
• Experience with end-to-end system-level testing in a manufacturing or production environment.

Responsibilities

• Design, build, and qualify electro-mechanical optical test stations for manufacturing-line integration, supporting build, test, and volume production of optical intersatellite link systems.
• Develop and execute end-to-end (E2E) test architectures that simulate operational environments for electro-optical systems, validating performance across thermal cycling (TC) and thermal vacuum (TVAC) profiles.
• Define and implement design validation test (DVT) plans for optical and opto-mechanical assemblies, ensuring structural and optical stability under environmental stress.
• Conduct optical metrology including wavefront error, boresight alignment, radiometric calibration, and pointing accuracy during thermal transitions.
• Leverage PCBA-level electrical knowledge to identify and diagnose failures that originate at the board level, including connector intermittencies, solder joint reliability issues, signal degradation, and power integrity anomalies that impact optical system performance.
• Lead root cause analysis (RCA) for opto-mechanical and electrical failures, including performance degradation, thermal drift, and structural anomalies identified during environmental stress testing and manufacturing screening.
• Drive design corrective actions and feed findings back into hardware design, manufacturing processes, and test system improvements to increase first-pass yield (FPY).
• Develop measurement processes and procedures for volume manufacturing and transfer them to the production team, ensuring repeatability and FPY targets are met.
• Write Python/MATLAB/LabVIEW scripts to automate data acquisition, environmental control, instrument communication, and test data analysis.
• Analyze complex test datasets to identify performance trends, correlate optical and electrical failures to root causes, and develop optimal strategies for resolving technical problems in testing and manufacturing.
• Develop new and improve existing optical measurement methods and test station architectures to increase automation, robustness, and throughput for industrialization-grade production.

Skills

Problem solving

Root cause analysis

Optical metrology

Thermal cycling/TVAC testing

System-level testing in manufacturing

Cross-disciplinary collaboration

Education

Bachelor's degree in engineering/physics

Master's degree or above in engineering/physics

Tools

Python

MATLAB

LabVIEW

Job description

Amazon Leo is expanding its electro-optical test architecture team to design, build, and qualify electro-mechanical optical test stations for manufacturing-line integration and volume production of optical intersatellite link systems.

You will develop end-to-end test environments, define DVT plans, and perform optical metrology and RCA to ensure robustness, repeatability, and high first-pass yield across thermal cycling and TVAC conditions. Proficiency in Python, MATLAB, and LabVIEW is expected.