Shield AI
Staff Software Engineer, GCS - Full Stack (R5192)
$150K–$230K
United States +4 · On-site · Staff · Full-time · Posted Jun 12, 2026
- Location
- United States
San Diego, California
Dallas, Texas
Washington, D.C.
Boston, Massachusetts - Experience
- Typically 7 years with a Bachelor’s degree; or 6 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience.
- Education
- BS/MS in Computer Science, Software Engineering, Computer Engineering, or equivalent practical experience.
About the job
Build and lead full-stack web-based ground control and command-and-control software for planning, operating, and debriefing unmanned missions.
What you'll do
- Design, develop, and field GCS/C2 applications, including mission planning, real-time controls, telemetry visualization, and post-mission debrief tools.
- Own technical direction and interfaces for major features; mentor engineers and collaborate with autonomy, operations, and external partners.
- Prepare and validate mission-ready systems, troubleshoot them during field tests and operations, and improve deployment and testing tools.
What they ask for
- BS/MS in Computer Science, Software Engineering, Computer Engineering, or equivalent practical experience.
- Typically 7 years with a Bachelor’s degree, 6 years with a Master’s degree, or 4 years with a PhD; equivalent work experience is also stated.
- Experience with modern frontend frameworks and responsive web applications, plus full-stack or backend development in C/C++, Python, TypeScript, or Go.
- Deep familiarity with networked and distributed systems; experience using AI-assisted development tools; ability to obtain a SECRET clearance.
Nice to have
- GIS, web mapping libraries, and spatial data visualization experience.
- Experience with video streaming, debrief systems, containerization, C2 standards, or working with flight operators and military stakeholders.
Pay
USD 150,000–230,000 per year (base salary)
Tools
React, TypeScript, Node.js, Go, C/C++, Python, PostgreSQL, PostGIS
AI focus
Use AI-assisted development tools to accelerate software design, implementation, debugging, testing, and code review, while maintaining engineering judgment and validating final decisions.
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