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Shield AI

Builds autonomous aircraft for defense

Senior Software Engineer - Autonomy Capabilities, Space

Robotics & Autonomous SystemsUpdated on Nov 14
Full-timeBoston, MA, USA

About the Job

Requirements

  • A BS or MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a similar degree, or equivalent practical experience.
  • Typically requires at least 5 years of related experience with a bachelor's degree, 4 years with a master's degree, 2 years with a PhD, or equivalent work experience.
  • Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems.
  • Significant background in one or several robotic technology areas related to control systems, motion planning, optimization, tactical behaviors, or distributed decision-making.
  • Significant experience with unmanned system technologies and accompanying algorithms, ideally in the space domain.
  • Experience with simulation tools and environments such as AFSIM, NGTS, or similar for testing and validation.
  • Ability to troubleshoot and optimize system performance.
  • Ability to obtain a Secret clearance or higher.

Responsibilities

  • Create autonomy capabilities for satellites and missile defense applications, including large-scale distributed optimization, automated tasking and scheduling, track fusion, RPO operations, and space vehicle motion and behavior planning.
  • Build capabilities from the ground up and integrate them onto new platforms, initially through shorter-term R&D efforts or aligned customer programs, with successful efforts potentially growing into larger multi-year programs.
  • Build and own autonomy behaviors that power products, taking responsibility for key components from design through deployment.
  • Turn complex mission needs into reliable, scalable software, balancing near-term delivery with long-term maintainability and performance.
  • Shape how autonomy capabilities are designed, integrated, and evolved across platforms.
  • Use advanced optimization strategies for large-scale distributed decision-making, task allocation, and resource scheduling in multi-satellite coordinated missions.
  • Employ approaches for weapons target assignment and motion planning for fleets of space vehicles and interceptors.
  • Pioneer topics in low-SWaP optimal control, tactical behavior management in cooperative and adversarial contexts, and information-aware planning.
  • Develop high-performance software modules that are well tested, have clear interfaces and span of control, and are ready for mid-to-high Technology Readiness Level insertions.
  • Collaborate with perception, planning, simulation, hardware, and flight-test teams to integrate autonomy solutions on real-world platforms.
  • Deploy autonomy capabilities to real space vehicles, analyze mission logs to verify software performance, and validate system operational effect.
  • Contribute to autonomy roadmaps by researching and prototyping algorithms, identifying tactical capability gaps, and proposing solutions.
  • Travel around 10–15% of the year to office locations, customer sites, and flight integration events.

Desired Qualifications

  • Experience across multiple aerospace domains, such as air, land, sea, and space.
  • Experience across methodologies from classical control through optimization and applied machine learning or reinforcement learning.
  • Background in collaborative behaviors and swarm robotics.
  • Familiarity with domain-relevant Department of Defense or government programs.
  • Hands-on experience supporting integration events, customer demonstrations, or live exercises.

About the Company

Shield AI

Builds autonomous aircraft for defense

Shield AI builds autonomous aircraft and flight software for military and allied defense customers, with a focus on operations where conventional remote control breaks down. Its Hivemind AI pilot handles decisions during a mission, while the V-BAT aircraft gathers intelligence and locates targets. Aircraft makers use its software tools to develop and test their own autonomy, and its Aechelon business supplies visual and sensor simulation for pilot training. The company earns money from aircraft sales, autonomy software and contracted engineering and operational services. Shield AI was founded in 2015 and is headquartered in San Diego, California.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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