Senior Staff Engineer, Survivability Materials
Shield AI is hiring a Senior Staff Engineer, Survivability Materials in Seattle, United States. It pays $170k-$250k a year and Level rates it ; you can apply on Shield AI.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- Level classifies it as a lead role.
- Level lists 659 other open roles at Shield AI.
AI in this role
Job Description:
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.
How we rate this
Senior Staff Engineer, Survivability Materials at Shield AI rates 36 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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