Software Developer VII with Security Clearance

General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems. We have an outstanding opportunity for a Principal AI Battle Management Lead in Poway, CA. This role blends strategic leadership with hands-on technical development, guiding the architecture, prototyping, and deployment of AI-enabled battle management systems across GA-ASI’s unmanned and collaborative combat aircraft portfolio.

The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous systems that enable unmanned aerial systems (UAS) to execute autonomous missions. The Principal AI Battle Management Lead will act as a technical authority, hands-on engineer, and customer-facing leader, shaping the next generation of autonomous mission execution and decision-support capabilities for the U.S. Department of War.

DUTIES AND RESPONSIBILITIES

• Set the technical vision and roadmap for AI-enabled battle management systems, aligning GA-ASI autonomy solutions with DoD Joint All-Domain Command and Control (JADC2) and Collaborative Combat Aircraft (CCA) initiatives.
• Lead cross-functional engineering teams in developing and integrating multi-agent autonomy, real-time decision-support, and adaptive mission planning capabilities.
• Serve as principal investigator and program lead for advanced R&D efforts in AI/ML for battle management.
• Interface directly with senior government customers, DARPA, AFRL, and DIU to translate mission needs into executable autonomy architectures.
• Provide capture and proposal support, including shaping technical volumes, white papers, and executive-level presentations.
• Partner with industry and academic collaborators to bring cutting-edge AI research into operational prototypes.
• Establish best practices for DevSecOps, MLOps, and mission assurance in autonomy software development.
• Guide testing and evaluation strategies, including simulation, SIL/HIL, and flight demonstrations of AI-driven battle management capabilities.
• Mentor and grow technical talent across the autonomy and AI teams.
• Ensure compliance with ITAR, export control, cybersecurity, and DoD acquisition regulations

We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.  Job Qualifications​​​​​Typically requires a bachelors degree, masters degree or PhD in computer science, information systems or related discipline and progressive software development experience as follows; fifteen or more years of experience with a bachelors degree, thirteen or more years of experience with a masters degree, or ten or more years with a PhD.  May substitute equivalent experience in lieu of education. Demonstrated track record leading development of battle management systems, C2 decision-support, or collaborative autonomy architectures in defense/aerospace. Expertise in reinforcement learning, multi-agent coordination, deep learning, probabilistic reasoning, and decision-theoretic planning. Strong customer-facing experience: ability to present to senior DoD stakeholders, influence CONOPS development, and shape technology roadmaps. Proven success in capture and proposal efforts, including technical volume authorship and program strategy. Strong leadership, communication, and interpersonal skills to inspire teams and build trusted relationships with customers. Hands-on expertise in:Languages: Python, C++, Java, or equivalentFrameworks: PyTorch, TensorFlow, Ray RLlib, or equivalentData/AI Tools: Scikit-learn, Pandas, NumPy, JAXSimulation/Integration: NTGS, AFSIM, or similarCloud/DevOps: Kubernetes, Docker, AWS/Azure GovCloudMLOps/DevSecOps: MLflow, GitLab CI/CD, secure software pipelines. Ability to obtain and maintain a Top Secret / SCI security clearance is required (active clearance strongly preferred).