About the role
Shield AI - Principal Engineer, State Estimation (R4602) Principal Engineer, State Estimation (R4602) United States / San Diego, California / Dallas, Texas / Boston, MA / Washington, DC / Remote X-BAT Division – X-BAT Engineering - Software / Full Time Employee / On-site apply for this job Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the 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: We are looking for an experienced state estimation engineer to design, develop, and support the deployment of safety-critical navigation solutions for aerospace platforms. This role requires deep expertise in state estimation theory, extensive practical experience implementing ownship navigation systems in the aerospace domain, and strong software development skills for production-quality navigation code. The engineer will design and implement a unified navigation architecture that supports traditional GNSS/IMU fusion while being extensible to all-source navigation strategies incorporating diverse sensing modalities for GPS-degraded and denied environments. What you'll do: Navigation System Architecture & Design: Establish navigation performance requirements and error budgets for safety-critical applications Support decomposition of navigation requirements into allocations for sensors, estimation algorithms, and software components Design detailed software architecture for state estimation implementations, including module interfaces and data flow Algorithm Development & Implementation: Design and implement Extended Kalman Filter algorithms for navigation applications, with broad understanding of state estimation theory and alternative filtering approaches Implement tightly-coupled and loosely-coupled GNSS/INS integration algorithms Integrate diverse sensing modalities (vision, RF, celestial etc.) into multi-sensor fusion framework for GPS-degraded environments Develop fault detection, isolation, and recovery (FDIR) strategies for navigation systems Implement integrity monitoring and protection level calculations for safety-critical operations Certification & Verification: Develop verification and validation test plans for navigation algorithms onduct performance analysis including Monte Carlo simulation, covariance analysis, and flight test data evaluation Document navigation system design, requirements allocation, and compliance evidence Support safety assessment activities including failure modes and effects analysis Technical Leadership: Provide technical guidance on navigation architecture and state estimation approaches Support trade studies evaluating navigation sensor suites and fusion strategies Mentor junior engineers on state estimation theory and implementation Required qualifications: MS or PhD in Computer Science, Software Engineering, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Applied Mathematics, or related field 15+ years of experience developing state estimation algorithms for aerospace navigation applications Demonstrated experience implementing GNSS/INS integration solutions Experience with safety-critical system development and certification processes Deep understanding of state estimation theory Experience implementing multi-sensor fusion algorithms in production systems Strong background in inertial navigation, GNSS positioning, and sensor error modeling Strong programming skills in C/C++ and Python/MATLAB for algorithm development and analysis Understanding of integrity monitoring, protection levels, and safety assessment methods Experience with requirements management and verification/validation processes for certifiable systems Understanding of GPS/GNSS signal structure, error sources, and performance characteristics Knowledge of IMU error models, calibration, and Allan variance analysis Familiarity with alternative navigation sensors (camera, RF ranging, celestial, etc.) Understanding of navigation performance metrics (accuracy, integrity, continuity, availability) Preferred qualifications: PhD in relevant field with focus on state estimation or navigation Direct involvement in certified navigation system development from requirements through flight test Experience with specialized navigation approaches (vision-aided navigation, terrain-referenced navigation, celestial navigation, etc.) Publications or patents in navigation or state estimation Experience with GPS/GNSS jamming and spoofing mitigation techniques Clearance eligible or active security clearance $270,000 - $400,000 a year #LI-SM1 #LF 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. 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