AI Autonomy Engineering SME

Responsibilities

• Design, architect, and implement autonomy capabilities for UAS, drone swarms, robotic platforms, and C2 ecosystems.
• Develop real-time algorithms for navigation, sensor fusion, cooperative behaviors, target recognition, mission execution, motion planning, mapping/SLAM, and multi-agent coordination.
• Deploy and optimize AI/ML models for real-time inference on embedded edge processors, ruggedized payloads, and resource-constrained autonomous platforms.
• Build simulation, modeling, digital-twin, hardware-in-the-loop, and flight-test environments for autonomy validation.
• Integrate autonomy software with DoD C2 systems, tactical networks, mission-planning tools, edge devices, and enterprise platforms.
• Develop APIs and data interfaces for observability, command execution, and human-machine teaming.
• Engineer resilient autonomy solutions for GPS denial, electronic warfare, adversarial conditions, degraded communications, and sensor degradation.
• Manage AI/ML model governance, versioning, auditability, deployment, monitoring, tuning, and sustainment.
• Lead vulnerability mitigation, patching, cybersecurity, and survivability improvements for autonomous systems.
• Lead and mentor AI/ML, robotics, and software engineers and advise program leaders, operators, mission owners, and technical authorities.
• Evaluate emerging autonomy technologies and drive experimentation and prototyping for fieldable capabilities.

Requirements

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Aerospace Engineering, or a similar STEM discipline; an advanced degree is preferred.
• 15+ years of engineering experience, including significant work in AI/ML, robotics, UAS autonomy, or multi-agent systems.
• Demonstrated experience developing autonomy capabilities for unmanned or robotic platforms in defense, commercial, aerospace, or research environments.
• Expertise in autonomy algorithms, including motion planning, path optimization, obstacle avoidance, mapping/SLAM, swarming, and multi-agent coordination.
• Experience with PyTorch, TensorFlow, JAX, ONNX, ROS/ROS2, MAVLink, PX4/ArduPilot, and autonomy stacks.
• Experience with Gazebo, AirSim, FlightGoggles, or equivalent simulation environments.
• Experience with NVIDIA Jetson, VPUs, tactical compute nodes, embedded Linux, data links, tactical protocols, mesh networks, and publish/subscribe architectures.
• Software engineering experience with Python, C++, real-time systems, containerization, DevSecOps, and CI/CD pipelines.
• Experience with Kubernetes, Helm, GitLab CI, ArgoCD, Terraform, Pulumi, and Ansible.
• Knowledge of AI/ML system security and DoD cybersecurity compliance.
• U.S. citizenship is required.
• Top Secret clearance is required, with the ability to obtain and maintain TS/SCI.

Benefits

• Remote work is available from any location.
• The role is scheduled for 40 hours per week and requires 25–50% travel.
• Benefits include medical, dental, vision, Health Savings Account options, 401(k) with company match, paid vacation, sick and personal leave, paid holidays, paid parental and military leave, disability coverage, life insurance, and other insurance programs.
• Employees may receive up to 160 hours of paid family leave in a rolling 12-month period if eligible.
• GDIT offers an AI-powered career tool, internal mobility support, professional growth opportunities, wellness packages, and a military-friendly workplace.