Principal Engineer, AI Infrastructure (R4941)

Shield AI builds autonomy systems for defense applications, including air, maritime, and space platforms operating in complex and contested environments.  

We are establishing a centralized AI and Data Platform organization responsible for the infrastructure that underpins autonomy development across Hivemind and other programs. This team owns the systems used to train models, run simulation, manage data, and deploy models to operational environments.  

We are seeking a Principal Engineer that will scale an initial architecture into a platform that supports multiple autonomy programs.  

Success in this role requires disciplined execution, delivering fast iteration for engineering teams while maintaining reliability, cost control, and architectural consistency as the system scales.  

The Principal Engineer is accountable for ensuring engineers can move efficiently from idea to trained model to deployed capability, and that infrastructure decisions reflect the realities of the domain, including simulation-driven development, continuously evolving multi-modal sensor data, and deployment to constrained and reliability-critical systems.  

This role spans the full lifecycle of autonomy development, training foundation models, running large-scale and multi-fidelity simulation, managing training data, evaluating models, and deploying optimized models to edge systems.  

A key part of this role is defining how these capabilities extend beyond internal use. This includes establishing how Shield AI delivers AI infrastructure in customer environments across on-premise, cloud, hybrid, and sovereign or nationally constrained environments.  

Shield AI builds autonomy systems for defense applications, including air, maritime, and space platforms operating in complex and contested environments.  

We are establishing a centralized AI and Data Platform organization responsible for the infrastructure that underpins autonomy development across Hivemind and other programs. This team owns the systems used to train models, run simulation, manage data, and deploy models to operational environments.  

We are seeking a Principal Engineer that will scale an initial architecture into a platform that supports multiple autonomy programs.  

Success in this role requires disciplined execution, delivering fast iteration for engineering teams while maintaining reliability, cost control, and architectural consistency as the system scales.  

The Principal Engineer is accountable for ensuring engineers can move efficiently from idea to trained model to deployed capability, and that infrastructure decisions reflect the realities of the domain, including simulation-driven development, continuously evolving multi-modal sensor data, and deployment to constrained and reliability-critical systems.  

This role spans the full lifecycle of autonomy development, training foundation models, running large-scale and multi-fidelity simulation, managing training data, evaluating models, and deploying optimized models to edge systems.  

A key part of this role is defining how these capabilities extend beyond internal use. This includes establishing how Shield AI delivers AI infrastructure in customer environments across on-premise, cloud, hybrid, and sovereign or nationally constrained environments.  

You will define the infrastructure that supports the development and deployment of autonomy systems across Shield AI.  

This role establishes the foundation for how models are trained, evaluated, and deployed, and directly impacts how quickly new capabilities are delivered into operational environments.  

You will have ownership over systems and decisions that are often distributed across multiple teams at other organizations, with the opportunity to shape how AI infrastructure is built and used both internally and in customer environments.