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An independent guide to Arizona’s AI economyData refreshed daily · Aug 18, 2026
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System Security Engineering (SSE) Program Lead - P4 (Onsite-Tucson, AZ)

RTX (Raytheon)Tucson, AZ107,500 USD - 204,500 USD

This position leads system security engineering across complex Department of Defense programs, guiding architects and engineering teams in the design, implementation, testing, and deployment of embedded and secure-system solutions. The program lead acts as a task and customer-facing leader, supporting reviews, technical exchanges, estimates, roadmaps, deliverables, reporting, earned value activities, and proposal efforts. Core work includes defining and flowing down security requirements, conducting threat modeling and Critical Program Information Assessments, addressing system-level risks, and ensuring compliance with technology-release and export-control policies. The role sits within Raytheon’s engineering and program organization and requires close coordination with customers, chief engineers, line management, and multiple technical disciplines. It suits an experienced defense security engineer or technical program leader who can influence stakeholders, make strategic tradeoffs, and lead teams in an agile environment. The position is fully onsite in Tucson, Arizona and requires U.S. citizenship with an active Secret clearance.

Requirements

Bachelor’s degree in a STEM field and typically 8 years of relevant experienceActive, transferable Secret clearance and U.S. citizenshipTechnical leadership experience in SSE, cybersecurity, reverse engineering, or embedded securityExperience delivering real-time embedded security solutions on DoD programsAbility to develop security requirements, architectures, plans, and implementation artifactsKnowledge of threat modeling, critical information protection, and DoD security policies
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Listed August 18, 2026 · Verify details with the employer before applying.

About RTX (Raytheon)

Tucson houses Raytheon's missile and defense HQ producing precision-guided systems, and has flight-tested an AI/ML-powered Radar Warning Receiver.