Senior Software Engineer, Autonomy Capabilities; R5339

Job Title

Tactical Autonomy Design Engineer

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. The Autonomy Capabilities Team develops functionality to automate single- and multi-agent teams of platforms in pursuit of mission objectives and acts as a central discipline-aligned focal-point for encouraging consistent usage of technical approaches across business portfolios.

This team operates at all levels of the command-and-control hierarchy (from advanced control laws, through motion planning, and up to advanced tactical behaviors and multi-agent coordination) and across a multitude of mission sets, platform types, and operational domains (e.g., air, sea, space). The team puts a strong emphasis on both fundamentals (e.g., aircraft kinematics/dynamics, trajectory design, optimization, information fusion, efficient algorithms, etc.)

and software integration skillsets (e.g. structures, protocols, threading, interface management, etc.) to bring market-differentiating capabilities to customers that seamlessly operate within their integration contexts. This position is perfect for an individual who enjoys solving complex problems across a diverse set of programs and integration contexts. An ideal candidate is expected to address operational system needs through a multitude of advanced methodologies that blend traditional control system approaches with advanced optimization.

Developed solutions are expected to be integrated into real-world platforms with near-term program impacts and rewards and so balancing theory with practice and rigorous implementation is paramount.

What You'll Do:

• Tactical Autonomy Design
  - Design tactical autonomy algorithms to enable unmanned aircraft to perform complex missions across air, land, and sea domains with minimal human supervision.
• High-Performance Software Development
  - Develop high-performance software modules that incorporate planning, decision-making, and behavior execution strategies for dynamic and adversarial environments.
• Behavior Architecture Implementation
  - Implement and test behavior architectures that enable multi-agent coordination, target engagement, reconnaissance, and survivability in contested scenarios.
• Hybrid Autonomy Integration
  - Work at the intersection of classical autonomy and machine learning, blending rule-based systems with learning-based methods such as reinforcement learning to achieve robust, adaptive behavior.
• Cross-Functional Collaboration
  - Collaborate with cross-functional teams including perception, planning, simulation, hardware, and flight test to ensure seamless integration of autonomy solutions on real-world platforms.
• Deployment & Field Testing
  - Deploy autonomy capabilities to real platforms and participate in field tests and flight demos, validating performance in operationally relevant conditions.
• Mission Data Analysis
  - Analyze mission logs and performance data to diagnose failures, optimize behavior models, and inform iterative development.
• R&D and Road mapping
  - Contribute to the autonomy roadmap by researching and prototyping new algorithms, identifying tactical capability gaps, and proposing novel solutions that advance Shield AI's mission.
• Program Support & Adaptation
  - Support defense-focused programs and customer needs by adapting autonomy solutions to evolving mission sets, compliance requirements, and operational feedback.
• Travel Requirement
  - Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight integration events).

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
• Typically requires a minimum of 5 years of related experience with a Bachelor's degree; or 4 years and a Master's degree; or 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 (RTOS)
• Significant background in one or several robotic technology areas related to control systems, motion planning, optimization, tactical behaviors, and/or distributed decision-making
• Significant experience with unmanned system technologies and accompanying algorithms (ideally in the space domain specifically)
• Experience with simulation tools and environments (e.g., AFSIM, NGTS, or similar) for testing and validation
• Strong problem-solving skills, with the ability to troubleshoot and optimize system performance
• Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary…