Lead survivability engineering for autonomous aircraft: design and optimize low-observable features, perform EM signature modeling and RCS testing, partner with multidisciplinary teams and materials scientists, translate threats into survivability requirements, and support assessments and milestone decisions throughout the program lifecycle.
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.
At Shield AI, we are building intelligent autonomous aircraft designed to operate and survive in highly contested environments. We are seeking a Survivability Materials Engineer to lead the selection, qualification, specification, and production implementation of low-observable and signature-control materials for next-generation autonomous aircraft.
This role is ideal for an engineer with experience in radar-absorbing materials, specialty coatings, electromagnetic material characterization, and aerospace manufacturing processes. You will work across survivability analysis, design engineering, manufacturing, quality, supply chain, and sustainment teams to ensure material solutions meet signature-performance requirements while remaining producible, inspectable, durable, and supportable throughout the aircraft lifecycle.
What you'll do:
- Conduct material surveys and evaluate radar-absorbing materials, conductive materials, dielectric materials, specialty coatings, adhesives, sealants, and other survivability-related material systems.
- Develop and maintain a survivability materials database containing performance, cost, supplier, part-number, availability, application, and sustainment information.
- Partner with survivability analysis, design, manufacturing, and program teams to down-select materials based on signature performance, durability, producibility, weight, cost, and supply-chain risk.
- Develop material qualification plans and oversee electromagnetic, electrical, mechanical, thermal, chemical, and environmental testing.
- Establish and maintain laboratory capabilities for material characterization, process development, receiving inspection, and production verification.
- Provide hands-on production support for material application, inspection, troubleshooting, repair, supplier coordination, and sustainment.
Required qualifications:
- B.S. or M.S. in Materials Science and Engineering, Chemical Engineering, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Physics, Chemistry, or a related technical discipline.
- 10+ years of experience in aerospace materials engineering, low-observable materials, electromagnetic materials, specialty coatings, or a related field.
- Working knowledge of radar-absorbing materials, conductive coatings, dielectric materials, adhesives, sealants, or specialty surface treatments.
- Understanding of how complex permittivity, complex permeability, conductivity, and thickness affect electromagnetic and radar-signature performance.
- Experience with material characterization, laboratory testing, production inspection, or supplier qualification.
- U.S. Citizenship and active Secret clearance required.
Preferred qualifications:
- Experience developing or qualifying radar-absorbing materials, low-observable coatings, structural RAM, conductive treatments, or signature-control appliqués.
- Experience measuring electromagnetic material properties using free-space, waveguide, coaxial, resonant-cavity, or reflectivity-based test methods.
- Familiarity with vector network analyzers, free-space measurement systems, conductivity equipment, coating-thickness instruments, environmental chambers, and mechanical test equipment.
- Active Secret, Top Secret, or SCI security clearance.
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
Lead multi-year strategic planning and annual operating cycles, evaluate portfolio tradeoffs, build financial models for capital allocation, and translate strategy into cross-functional execution plans with KPIs. Conduct market sizing, competitive analysis, scenario modeling, and track performance through operating cadences to identify bottlenecks and recommend solutions.
Top Skills:
AechelonHivemindV-BatX-Bat
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Develop state estimation and navigation algorithms for autonomous systems operating in GPS-denied environments. Build production-grade C++ software for embedded Linux robotic platforms, create modeling and simulation tools, and implement comprehensive testing and validation. Collaborate on roadmap planning and agile execution while improving benchmarking and performance-analysis pipelines. The role requires professional C++ expertise, state estimation algorithm experience, sensor-fusion familiarity, and the ability to deploy reliable autonomy software.
Top Skills:
Automated TestingBarometersC++CamerasCeresCi PipelinesEkfEmbedded LinuxGpsGraph-Based OptimizationGtsamImuLaser AltimetersMagnetometersMatlabOpenvinsParticle FiltersPythonSlamUkfVio
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Develop deep learning and 3D computer vision models for state estimation, visual navigation, localization, depth, correspondence, and pose estimation. Own data preparation, training, evaluation, benchmarking, and reproducible workflows. Integrate learned measurements into VIO and terrain-relative navigation systems, optimize models for onboard compute, and collaborate with deployment, software, systems, and flight-test teams to deliver production-ready Hivemind SDK components.
Top Skills:
3D Computer VisionDeep LearningDiffusion ModelsEmbedded Compute PlatformsFlow MatchingGpu ComputingModel QuantizationMulti-View GeometryOnnxPythonPyTorchSensor Data PipelinesSlamStructure From Motion (Sfm)TensorrtVisual-Inertial Odometry (Vio)
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
