Principal AI Autonomy Systems Integrator (UAS / SWARMING / C2 / EDGE AI) at General Dynamics in Any Location
- Company: General Dynamics
- Location: Any Location / Remote
- Salary: $149K – $201K
- Job type: full time
- Workplace: remote
- Posted: 2026-10-12
All open roles at General Dynamics
Job description
Type of Requisition: Regular Clearance Level Must Currently Possess: Top Secret/SCI Clearance Level Must Be Able to Obtain: Top Secret/SCI Public Trust/Other Required: None Job Family: Data Science and Data Engineering Job Qualifications: Skills: Artificial Intelligence Technologies, Design, Sensor Fusion, Sensors, Unmanned System Certifications: None Experience: 10 + years of related experience US Citizenship Required: Yes Job Description: PRINCIPAL AI AUTONOMY SYSTEMS INTEGRATOR (UAS / SWARMING / C2 / EDGE AI) Hands‑On Engineering • Autonomous System Integration • Mission‑Thread Enablement Itegrate autonomy software with real assets, validate behaviors in simulation and field environments, and ensure that autonomous agents act over trusted data, in real time, under real mission pressures. MISSION & IMPACT Autonomy Integration & System Engineering Integrate autonomy stacks onto UAS, multi‑vehicle swarms, and robotic platforms, including navigation, perception, cooperative behaviors, and distributed decision-making. Implement real‑time autonomy pipelines that incorporate sensing, fusion, planning, and control across diverse air/ground systems. Adapt and optimize autonomy algorithms for constrained edge environments (embedded systems, GPUs/VPUs, tactical compute nodes). Data‑ and Knowledge‑Aligned Autonomy Build data pipelines and semantic alignment layers so autonomous systems operate against trusted, structured, and meaning‑preserving data representations . Integrate autonomy with ontology-driven or schema-governed data models to ensure consistent entity tracking, mission-state representation, and decision context. Enable retrieval‑grounded behaviors where autonomous agents act based on authoritative, updated, and fused situational information. Edge Deployment Across Contested Environments Deploy AI/ML models and autonomy services to edge compute environments (K3s/RKE2, containers, bare metal). Harden autonomy behaviors for degraded communications, GPS denial, EW threats, sensor loss, and variable latency. Implement resilient synchronization patterns between edge devices and enterprise/tactical nodes. Simulation, Experimentation, and Field Testing Conduct structured field experiments with unmanned vehicles, swarms, multi‑agent behaviors, and C2 workflows. Validate mission‑thread performance across detection, tasking, coordination, and operator-in-the-loop behaviors. Agentic Workflow Integration Integrate agent frameworks enabling autonomy agents to plan, coordinate, task, and interact with mission tools and human operators. Define safety gates, oversight mechanisms, and deterministic tool‑use patterns that support “human‑on‑the‑loop” operations. Support multi‑agent cooperation through standard APIs and interoperable messaging patterns. C2, Networks, and Cross‑Domain Integration Integrate autonomous systems with tactical C2 platforms, data links, secure communications, and multi‑domain operational workflows. Implement open standards (MOSA, SOSA, CMOSS, open messaging protocols) for plug‑and‑play component integration. Enable interoperability across joint, partner‑nation, and coalition environments with appropriate policy controls. WHAT YOU WILL DO Build full autonomy pipelines end‑to‑end, from sensing through action execution. Deploy CV, tracking, SLAM, pattern‑learning, anomaly detection, and cooperative‑agent models on real unmanned systems. Integrate heterogeneous sensors, radios, and payloads with autonomy decision loops. Conduct troubleshooting and rapid problem resolution across autonomy software, embedded systems, edge clusters, and C2 interfaces. Translate mission problems into executable autonomy behaviors and scenario‑specific workflows. Train teams and mission personnel on system configuration, safety, deployment, and best practices. REQUIRED EXPERIENCE Core Background Education: BA/BS or equivalent Experience: 10+ years in unmanned systems, autonomy engineering, robotics integration, or embedded AI/ML deployment. D
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