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Shield AI

Builds autonomous aircraft for defense

Staff Software Engineer - Autonomy Capabilities

Robotics & Autonomous SystemsUpdated on Nov 14
Full-time

About the Job

Requirements

  • A BS, MS, or PhD in Computer Science, Aerospace Engineering, Electrical Engineering, Robotics, Mechanical Engineering, or a related field is required.
  • Proficiency in production-level C++ software development is required.
  • At least 7 years of experience in software subsystem scheduling and integration, behavior planning, task and resource allocation, motion planning, optimization, or flight controls is required.
  • Experience with collaborative software development tools for version control, issue tracking, code reviews, and release management is required.
  • Ability to lead multidisciplinary teams, set technical direction, and manage full project lifecycles from concept to deployment is required.
  • Ability to learn and grow individually, mentor junior team members effectively, and build team cohesion and capacity is required.
  • Ability to act as the technical owner for an entire software system, including stakeholder engagement, requirements definition, roadmap management, team coordination, design, implementation, sustainment, and evolution is required.
  • Eligibility to obtain and maintain an active U.S. Secret security clearance is required.
  • A desire to work in a collaborative, fast-paced, enthusiastic, and mission-centric environment is required.

Responsibilities

  • Design tactical autonomy algorithms that enable unmanned aircraft to perform complex missions across air, land, and sea domains with minimal human supervision.
  • Develop high-performance software modules incorporating planning, decision-making, and behavior execution strategies for dynamic and adversarial environments.
  • Implement and test behavior architectures for multi-agent coordination, target engagement, reconnaissance, and survivability in contested scenarios.
  • Integrate classical autonomy and machine learning by blending rule-based systems with learning-based methods such as reinforcement learning to achieve robust, adaptive behavior.
  • Collaborate with perception, planning, simulation, hardware, and flight-test teams to integrate autonomy solutions on real-world platforms.
  • Deploy autonomy capabilities to real platforms and participate in field tests and flight demonstrations to validate performance in operationally relevant conditions.
  • Analyze mission logs and performance data to diagnose failures, optimize behavior models, and inform iterative development.
  • Research and prototype new algorithms, identify tactical capability gaps, and propose solutions that advance the autonomy roadmap.
  • Support defense-focused programs and customer needs by adapting autonomy solutions to evolving mission sets, compliance requirements, and operational feedback.
  • Travel approximately 10–15% of the year to office locations, customer sites, and flight-integration events.

Desired Qualifications

  • Experience across a breadth of technology readiness levels and ability to bridge concepts from research-grade to operationally ready.
  • Experience with mission systems integration, ideally including hands-on support for integration events or flight demonstrations.
  • Experience in collaborative mission planning, behavior planning, or synchronized teaming.
  • Experience in automated red-force versus blue-force tactics.
  • Experience in motion planning across vehicle classes, kinematic constraints, and team compositions.
  • Experience in weapons target assignment, sensor target pairing, or sensor-centric control laws.
  • Experience in collision avoidance, geofencing, or safety monitoring.
  • Experience in more than one operational effect, such as strike, air combat, surveillance, or reconnaissance, and more than one associated domain, such as air, space, maritime, or ground.
  • Experience with free and open-source software commonly used in robotic systems, such as ROS, OMPL, and optimization solvers.
  • Experience with simulation tools and environments, such as AFSIM and NGTS, for testing and validation.
  • Familiarity with practical aspects of navigation and communications systems.
  • Experience across the product delivery lifecycle, from emerging opportunity through system acceptance, deployment, and sustainment.
  • Familiarity with systems engineering methodologies.
  • Familiarity with high-assurance software development processes, such as DO-178C or equivalent military standards.

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
Series H
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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