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You will collaborate with research engineers, user experience teams, designers, hardware and software developers to define, develop, and verify the customer-facing attributes and performance capabilities of ADAS features.</p>\n<p>Your responsibilities will include defining and documenting vehicle-level acceptance criteria for ADAS features, leading/supporting the development of verification plans and verification methods, collaborating with global functional partners to meet system and vehicle level performance requirements, and cascading system-level requirements to functional partners.</p>\n<p>You will also lead/support the development and sign-off of ADAS features on vehicle programs, support feature calibration studies to satisfy vehicle-level performance requirements, develop MATLAB and CAN tools for data collection and analysis, identify opportunities to utilize HiL and CAE methods for feature calibration and performance verification, plan and execute real-world evaluations of ADAS features via vehicle/HIL/virtual testing and identify system problems and issues, and support and coordinate root-cause analysis with internal functions and external suppliers to ensure delivered system achieves feature requirements.</p>\n<p>You will benchmark competitors and monitor public domain requirements.</p>\n<p>You will have a Bachelor&#39;s degree in Electrical Engineering, Mechanical Engineering, or a related technical field, and experience in developing features in the Driver Assistance domain using radars, cameras, lidars, ultrasonic sensors and other related vehicle systems (body, electrical, chassis, powertrain).</p>\n<p>Familiarity with actuators and control systems is also required.</p>\n<p>A Master&#39;s degree in Engineering (Electrical, Mechanical, Aerospace, Mechatronics, Software, Computer Science, AI, Systems Engineering, Product Development) or a related technical field is preferred, as well as experience applying Systems Engineering principles, experience with robotic verification and testing methods, troubleshooting experience with electromechanical systems, experience with differential GPS equipment, experience using typical automotive interfaces: CAN, CANFD, Autosar, Auto-Ethernet, etc., experience using Vector CANape, CANalyzer and dSPACE Controls Desk or similar tools, experience with Matlab/Simulink, experience in verification techniques (design verification methods, vehicle data acquisition/analysis), experience with virtual validation methods (HIL/MIL/SIL), strong leadership skills, passion for quality, passion to improve customer satisfaction, good communications and project management skills, strong oral &amp; 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As we push the boundaries of what&#39;s possible in contested environments, we are looking for a Lead Survivability Engineer to shape and optimize the low observable (LO) performance of our next-generation autonomous aircraft.</p>\n<p>This role is ideal for an experienced engineer with deep expertise in radar cross-section (RCS) shaping, LO materials, and electromagnetic signature modeling who thrives in a fast-paced, mission-driven environment. You&#39;ll work across disciplines to ensure our aircraft can survive, evade, and complete missions in highly contested airspace.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Design and optimize low observable (LO) features across the airframe focusing on shaping, edge treatments, radar-absorbing materials, and subsystem integration.</li>\n<li>Conduct modeling and simulation of electromagnetic signatures using industry-standard tools such as HFSS, CST Studio Suite, Xpatch, and SENTRi.</li>\n<li>Work with multidisciplinary teams in propulsion, avionics, structures, and AI to ensure survivability is baked into the system architecture from day one.</li>\n<li>Lead or support signature testing efforts, including indoor and outdoor RCS range tests, validation campaigns, and supplier-level hardware evaluations.</li>\n<li>Translate mission threats and requirements into survivability features that address RCS, thermal, visual, and acoustic observability constraints.</li>\n<li>Partner with materials scientists to mature radar-absorbing coatings and structural RAM for manufacturability and field durability.</li>\n<li>Support internal and customer assessments, threat modeling reviews, and milestone decisions throughout the program lifecycle.</li>\n</ul>\n<p><strong>Requirements:</strong></p>\n<ul>\n<li>B.S. or M.S. in Aerospace Engineering, Electrical Engineering, Physics, or a related discipline.</li>\n<li>7+ years of hands-on experience in LO or survivability engineering, preferably on tactical aircraft, UAVs, or stealth systems.</li>\n<li>Proficiency with EM simulation tools such as HFSS, CST, Xpatch, or SENTRi.</li>\n<li>Strong understanding of RCS shaping principles, edge treatments, cavity suppression, and materials integration.</li>\n<li>Practical experience with LO testing methods and RCS measurement equipment.</li>\n<li>Familiarity with radar-absorbing materials (RAM), LO coatings, and structural LO trade studies.</li>\n<li>Solid collaboration and communication skills with the ability to work across design, test, and manufacturing teams.</li>\n<li>U.S. Citizenship and active Secret clearance required (TS/SCI preferred).</li>\n</ul>\n<p><strong>Preferred Qualifications:</strong></p>\n<ul>\n<li>Experience with military UAV platforms or 5th-gen fighter programs.</li>\n<li>Background in survivability analysis in contested environments (e.g., IADS, radar networks).</li>\n<li>Familiarity with platform CONOPS, threat modeling, and mission-level survivability assessments.</li>\n<li>Ability to contribute to the design, test, and fielding of a fully integrated LO platform.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b417d598-574","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Shield AI","sameAs":"https://www.shield.ai","logo":"https://logos.yubhub.co/shield.ai.png"},"x-apply-url":"https://jobs.lever.co/shieldai/0ea1cea2-6bb5-40e9-a3ca-c9ab45498454","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$168,476 - $252,714 a year","x-skills-required":["Radar Cross-Section (RCS) Shaping","Low Observable (LO) Materials","Electromagnetic Signature Modeling","HFSS","CST Studio Suite","Xpatch","SENRi","Low Observable (LO) Testing Methods","Radar-Absorbing Materials (RAM)","LO Coatings","Structural LO Trade Studies"],"x-skills-preferred":["Military UAV Platforms","5th-Gen Fighter Programs","Survivability Analysis in Contested Environments","Platform CONOPS","Threat Modeling","Mission-Level Survivability Assessments"],"datePosted":"2026-04-17T13:06:40.508Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dallas"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Radar Cross-Section (RCS) Shaping, Low Observable (LO) Materials, Electromagnetic Signature Modeling, HFSS, CST Studio Suite, Xpatch, SENRi, Low Observable (LO) Testing Methods, Radar-Absorbing Materials (RAM), LO Coatings, Structural LO Trade Studies, Military UAV Platforms, 5th-Gen Fighter Programs, Survivability Analysis in Contested Environments, Platform CONOPS, Threat Modeling, Mission-Level Survivability Assessments","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":168476,"maxValue":252714,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_faac35f0-1f9"},"title":"Hardware Reliability Engineer II","description":"<p>As a Hardware Reliability Engineer II at Shield AI, you will support efforts to ensure the robustness and long-term performance of our VBAT flight hardware. 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