Own the V-BAT unmanned aircraft system reliability model and failure-prediction strategy. Build fault trees, analyze field and test data, identify single points of failure, guide design-for-reliability decisions, lead root-cause investigations and corrective actions, manage reliability testing and production screening, and track MTBF, failure-rate trends, and reliability growth for leadership.
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.
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.
- 5+ years of 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.
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
###
Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
Similar Jobs at Shield AI
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Senior technician responsible for inspecting, troubleshooting, repairing, modifying, and maintaining V-BAT Ground Support Equipment. Perform electrical, electronic, mechanical diagnostics and repairs, construct and test wiring harnesses, complete maintenance documentation, support root-cause investigations, improve procedures, and assist with aircraft-level maintenance when workload allows.
Top Skills:
Connector RepairContinuity TestingCrimpingDigital MultimeterElectronic Maintenance/Work-Order Management SystemsFaa Airframe And Powerplant (A&P)Insulation TesterIpc-A-610Ipc/Whma-A-620J-Std-001Load-Testing EquipmentMS OfficePower SupplyResistance TestingSolderingVoltage TestingWiring Harness Repair
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Own full-cycle recruiting for highly specialized software engineering roles spanning autonomy, robotics, embedded software, perception, planning, distributed systems, simulation, machine learning, and infrastructure. Develop sourcing strategies, advise engineering leadership on talent markets and workforce planning, manage complex pipelines, improve recruiting processes and tooling, deliver strong candidate experiences, and mentor junior recruiters.
Top Skills:
Ats SystemsHivemindRecruiting AnalyticsSourcing Platforms
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Maintain an authoritative ledger of ground support equipment and payloads, build analytical infrastructure (dashboards, forecasts, lifecycle models), provide fleet allocation and deployment planning support, coordinate with Engineering/Manufacturing/Sustainment, and produce decision-ready briefings and ad hoc analyses for senior leadership to inform asset management and capture activities.
Top Skills:
ExcelPower BISQLTableau
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

