Shield AI
Staff Engineer, Safety - X-BAT (R5312)
Dallas, Texas · Staff+ · Part-time
Sponsorship not specified$140k-$210kDetected 13 days ago
RecruitingMIL-STDSystems EngineeringCommunication
About the role
- Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft.
- For more information, visit www.shield.ai.
- Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Responsibilities
- Work with System-Safety / Airworthiness Lead to derive, refine, and validate safety requirements for the X-BAT platform and support systems.
- Support development of the safety case and certification evidence for X-BAT.
- Partner with cybersecurity specialists to develop and validate cybersecurity related safety requirements.
- Collaborate with Systems Engineering to audit, refine, and assure the X-BAT Hazard Tracking System, ensuring accuracy, traceability, and closure of hazards.
- Support mishap and near miss investigations for the X-BAT platform, providing technical system-level context.
- Participate in design reviews, safety working groups, and change boards to ensure safety considerations are integrated early in the design lifecycle.
- Contribute to risk assessments and support readiness reviews for test, integration, and operational events.
- The Safety Engineer for the X-BAT program will support the development, integration, and verification of system-level safety requirements for this revolutionary next-generation platform.
- This role bridges engineering design, system safety analysis, airworthiness, and cybersecurity by interrogating technical systems, driving hazard analyses, and ensuring requirements are implemented correctly.
- You will collaborate closely with the System-Safety /Airworthiness Lead, Systems Engineering, and technical Responsible Engineers to maintain the safety baseline and Hazard Tracking System for X-BAT.
Requirements
- Bachelor's degree in engineering (systems, aerospace, electrical, mechanical, or related field).
- 5-8+ years of experience in system safety, airworthiness, or mission-critical system engineering.
- Working knowledge of system safety processes and hazard analysis tools.
- Familiarity with requirements management and hazard tracking systems.
Nice to have
- Prior experience with UAS or autonomous aircraft platforms.
- Experience with MIL-STD-882, ARP-4761, STANAG safety frameworks, or similar.
- Familiarity with cybersecurity requirements for safety-critical systems.
- Experience generating or maintaining hazard logs (HTS/Hazard Tracking Systems).
- Experience working in fast-paced development or prototyping environments.
- All offers are contingent on a cleared background and possible reference check.
- 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.
Compensation
- #LI-JM1 #LD 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)
Benefits
- Military fellows and part-time employees are not eligible for benefits.
- 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.
Company info
- Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems.
- With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide.
Equal opportunity
- equal opportunity workplace and is an affirmative action employer.
- If you have a disability or special need that requires accommodation, please let us know.
Apply directly at Shield AI →Create a free account for alerts like thisView Shield AI immigration profile
This listing is sourced directly from Shield AI's careers page and normalized into a canonical job model.