Staff Engineer, System Reliability (R5533)

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 .

Job Description:

Shield AI is looking for a Reliability Modeling Engineer to own the reliability model and failure-prediction strategy for the V-BAT unmanned aircraft system. In this role you will build the quantitative backbone that predicts how the system fails, why it fails, and how to design those failures out — translating field data, industry sources, and test results into models that directly inform design, production, and sustainment decisions. You will be the reliability subject-matter expert who partners across Design, Manufacturing, Quality, and Fleet Support to drive measurable improvements in system reliability.

What you'll do:

• Build and maintain the V-BAT system reliability model, predicting system-level failure rate using failure-rate data from the field and industry sources.
• Create and maintain the V-BAT system fault tree, identifying single points of failure and quantifying their contribution to overall system reliability.
• Inform design decisions that eliminate single points of failure and improve the reliability of the system, providing Design-for-Reliability (DfR) guidance in design reviews.
• Partner with Design, Fleet Support, Quality, and Manufacturing Engineers on root cause investigations for field failures, and drive corrective and preventive actions to closure.
• Drive reliability test campaigns in production and sustainment to verify the system is meeting its reliability requirements and predictions, feeding results back into the model.
• Drive production reliability screening campaigns to reduce infant-mortality failures, such as HASS (Highly Accelerated Stress Screening) and ESS (Environmental Stress Screening).
• Establish and track reliability metrics — MTBF, failure-rate trends, and reliability growth — and communicate reliability status and risk posture to program leadership.

Required qualifications:

• B.S. in Engineering, Mathematics, or Statistics discipline.
• Typically requires a minimum of 7 years of related experience in reliability or surety engineering in a high-consequence industry (defense, aerospace, automotive, or medical device).
• Expertise in Fault Tree Analysis (FTA), Failure Modes, Effects, and Criticality Analysis (FMECA), and Mean Time Between Failure (MTBF) calculations.
• Demonstrated ability to build reliability models from field and test data and translate them into actionable design and production decisions.

Preferred qualifications:

• Experience with Reliability, Availability, and Maintainability (RAM) modeling and Weibull analysis.
• Experience with reliability analysis software such as Relyence (or equivalent tools such as ReliaSoft/Weibull++, Windchill Risk & Reliability).
• Familiarity with government standards for developing reliability and maintainability models, such as MIL-HDBK-217, 217Plus, and MIL-STD-756.
• Experience implementing FRACAS (Failure Reporting, Analysis, and Corrective Action System) and supporting Failure Review Boards.
• CRE (ASQ Certified Reliability Engineer) certification.
• Experience with unmanned aircraft, aerospace, or other mission-critical hardware systems.