Staff Software Engineer, Space Autonomy & Optimization

Shield AI; Washington (District of Columbia); On-site; USD 188,000 - 281,000; Full time

Job summary

Shield AI is a defense-technology company developing autonomy solutions for space and mission-critical platforms. The Autonomy Capabilities Team focuses on automating multi‑agent systems and integrating advanced algorithms into real-world platforms.

The Staff engineer role leads technical delivery and shapes requirements for scalable autonomy solutions across diverse programs. The position emphasizes balancing theoretical rigor with practical implementation, enabling near‑term impact while

Qualifications

• Minimum 7 years of related experience with a Bachelor's degree; or 6 years with a Master's; or 4 years with a PhD.

Responsibilities

• Apply multi-objective optimization for distributed decision making, task allocation, and scheduling across satellite missions.
• Develop target assignment and motion planning for space fleets and interceptors.
• Pioneer advanced low-SWaP control, tactical behaviors, and information-aware planning.
• Develop high-performance, well-tested software modules with clear interfaces.
• Collaborate with perception, planning, simulation, hardware, and flight-test teams to ensure integration.
• Deploy capabilities to space vehicles and analyze mission logs to verify performance.
• Contribute to autonomy roadmaps by researching and prototyping new algorithms.
• Travel 10-15% of the year to office locations and customer sites.

Skills

C++

Python

RTOS

Problem solving

Communication

Teamwork

Security clearance readiness

Education

Bachelor's degree

Master's degree

PhD

Tools

AFSIM

NGTS

Job description

Shield AI is a defense-technology company developing autonomy solutions for space and mission-critical platforms. The Autonomy Capabilities Team focuses on automating multi‑agent systems and integrating advanced algorithms into real-world platforms.

The Staff engineer role leads technical delivery and shapes requirements for scalable autonomy solutions across diverse programs. The position emphasizes balancing theoretical rigor with practical implementation, enabling near‑term impact while