Shield AI

Senior Software Engineer, Autonomy Capabilities – Maritime (R5339)

$160K–$240K

Boston, Massachusetts +3 · On-site · Senior · Full-time · Posted Aug 26, 2026

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Location: Boston, Massachusetts
Washington, D.C.
San Diego, California
Dallas, Texas
Experience: Typically 10 years with a Bachelor’s degree; 9 years with a Master’s degree; 7 years with a PhD; or equivalent work experience.
Education: BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience.

About the job

Develop and deploy maritime autonomy capabilities for unmanned surface and underwater vehicles and cooperating UAVs, including multi-agent missions to locate and pursue targets while avoiding hazards.

What you'll do

Build motion-planning, localization, tracking, safety, and multi-agent coordination capabilities for maritime operations.
Develop, test, integrate, and deploy high-performance autonomy software on real-world platforms; support demonstrations and analyze mission logs.
Research and prototype algorithms, contribute to autonomy roadmaps, and mentor junior engineers.

What they ask for

BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a similar degree, or equivalent practical experience.
Proficiency in C++ and Python.
Significant experience in robotics areas such as control systems, motion planning, optimization, tactical behaviors, or distributed decision-making, and with unmanned systems.
Experience with simulation tools for testing and validation; ability to obtain a SECRET clearance or higher.

Nice to have

Experience across multiple domains, applied ML/RL, collaborative behaviors, or swarm robotics.
Experience with DoD or government programs, integration events, customer demonstrations, live exercises, or applied R&D.

Pay

USD 160,000–240,000 (per-year-salary) base salary

Tools

C++, Python, AFSIM, NGTS

AI focus

Develop autonomy for search, localization, pursuit, safe maneuvering, and heterogeneous multi-agent mission coordination. Applied ML/RL is preferred experience.

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