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Shield AI

Staff Engineer, Reliability Test (R5532)

Seattle, Washington

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hirly's read of this role

Role family
Engineering
Seniority
Lead / management
Stated salary
$120,000 – $180,000 per year
Country
US
Work mode
On-site / unstated
First seen by hirly
11 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube .

As a Reliability Test Engineer at Shield AI, you'll prepare, execute, and manage environmental tests on electronic flight hardware across the VBAT and XBAT aircraft, ensuring it meets performance requirements through rigorous thermal, vibration, shock, humidity, and altitude testing. This is a highly hands-on role. Working with design and reliability stakeholders, you'll define test plans — stress profiles, sample sizes, and pass/fail criteria — then bring them to the bench: designing and modeling test fixtures in CAD, instrumenting hardware with thermocouples, accelerometers, strain gauges, and humidity sensors, configuring data acquisition, and programming and loading chambers. You'll frequently run several campaigns at once, owning the equipment scheduling needed to keep them moving without compromising data quality.

Once tests are running, you'll operate the equipment, monitor for and investigate failures, and reduce and document results in clear reports — including the plots and visualizations stakeholders rely on to make disposition and qualification decisions. You'll work with cutting-edge deep-tech hardware, collaborate across disciplines, and directly influence product quality and long-term reliability over the vehicles’ lifecycles.

Original posting on Shield AI's site ↗

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