Shield Senior Engineer, Software for Autonomous Aircraft Integration at Shield AI responsible for developing and integrating autonomy software onto unmanned platforms. Owns software end-to-end from simulation to live test exercises.
Responsibilities
Develop & Field Autonomy — Develop & integrate autonomy software solutions onto unmanned platforms (air, maritime, space, or effects/expendables), including payload computer bring-up, container-based deployment (e.g., k3s/k3d), and configuration across onboard compute, sensors, and command-and-control interfaces.
Collaboration Across Teams — Work closely with the Autonomy Capabilities team (motion planning, tactics), the Perception team, feature crews, and external partners (platform integrators, vehicle/autopilot control vendors, C2 providers) to deliver and validate mission-critical functionality on time.
Pre-deployment Preparation — Own the build, configuration, and validation process for mission-ready systems; coordinate hardware/software compatibility, mission readiness, and release cadence with capability and feature teams.
On-site Test & Mission Support — Travel to test sites and support live mission operations (flight tests, range exercises, on-water trials, integration events), including safety checks, system bring-up, and troubleshooting under time-critical constraints.
Hardware/Software Debugging — Diagnose and resolve integration issues across complex autonomy stacks, payload computers, and embedded systems in lab and field environments — including memory, CPU, and timing profiling under operationally-representative loads.
Mission Data & Debrief Support — Capture mission and test data, reproduce issues in simulation, and partner with autonomy capability owners to drive fixes back into the next build.
Continuous Improvement — Build tools and processes to improve integration timelines, test/mission reliability, and team efficiency across deployment cycles.
C2 Interoperability & Standards — Implement and validate compliance with command-and-control standards (e.g., A-GRA, UCI, OMS) and coordinate with C2 providers on interface contracts and integration milestones.
Travel Requirement – Members of this team typically travel around 10-20% of the year (to different office locations, customer sites, and integration/test events).
Qualification
BS/MS in Computer ScienceProficiency in C++Familiarity with middlewareHands-on experience supporting demosStrong problem-solving skillsAbility to obtain a SECRET clearanceProficiency in Python for scriptingFamiliarity with autonomy stacksBuild-system experience (e
Required
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 C++, with experience developing or integrating real-time or latency-sensitive systems.
Proficiency in Linux-based development and experience working with embedded systems, shell scripting, and system diagnostics.
Familiarity with middleware, pub-sub, or IPC frameworks used in autonomy or robotics systems (e.g., DDS, ActiveMQ).
Hands-on experience supporting demos, exercises, or field/mission tests for unmanned or autonomous systems.
Experience with autonomy simulation environments for testing and validation.
Strong problem-solving skills, with the ability to troubleshoot and optimize system performance across the full stack.
Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment.
Ability to obtain a SECRET clearance.
Preferred
Direct experience supporting uncrewed systems (air, maritime, space, ground, or effects/expendables) or similar field test campaigns.
Proficiency in Python for scripting, automation, and analysis.
Familiarity with autonomy stacks, motion planning, or vehicle-control integration.
Competence in vehicle electronics bring-up (avionics, spacecraft buses, or vessel control), payload computer integration, or hardware-in-the-loop debugging.
Experience with container orchestration (e.g., k3s, k3d, Docker) on embedded or payload compute.
Familiarity with platform control / autopilot stacks (e.g., PX4, ArduPilot, spacecraft flight software, vessel autopilots).
Proficiency in developing automation tools for system testing, logging, and data parsing.
Build-system experience (e.g., Conan, CMake) and CI/CD pipeline familiarity.
