Scout AI

Full-stack Engineer

• Designing and advancing the agent harness (agent loop, tools, prompts, execution environment, capabilities) used across Scout AI's agentic stack.
• Integrating fullstack software with physical hardware systems and AI agents—ensuring robust, low-latency communication across complex pipelines.
• Building simulation environments and video-game-like frameworks that allow agents to be tested and trained before physical deployment.
• Owning the connectors between AI models and real-world systems—the layer that translates model output into physical action.
• Fine-tune frontier AI models and build the data acquisition pipelines that feed the training infrastructure powering our agents.
• Work shoulder-to-shoulder with warfighters to turn capability requests into production-ready agentic systems — fast.

Staff Software Engineer – Agent Harnessing

AI Research Scientist

• Conduct original research in embodied AI, including learning from warfighter demonstration, reinforcement learning, memory, reward, vision-language modeling, and world modeling
• Build, test, and benchmark large-scale models for perception, decision-making, and control in simulated and physical environments
• Investigate transfer learning and continual learning paradigms across diverse robotic domains
• Collaborate with engineering, robotics, and field teams to integrate research into operational systems
• Lead research strategy and roadmap across key areas of autonomy and machine learning
• Support field tests and data collection campaigns to evaluate system performance in realistic environments

Senior AI Researcher

AI Engineer

• Design, train, and evaluate multimodal foundation models that enable multi-robot mission execution
• Drive model development decisions including model architectures, data mixtures, curriculum design, and training recipes informed by rigorous experimentation
• Curate and generate large-scale training datasets from both synthetic and real-world data engines
• Develop memory, communication, planning, and tool-use capabilities for AI agents operating across teams of robots
• Be obsessed with evaluation: design benchmarks, metrics, and testing methodologies that enable rapid iteration across the team
• Build and improve simulation environments targeted for synthetic data generation, evaluation, and reinforcement learning
• Translate foundational research into deployable, real-time perception and decision-making systems
• Collaborate across engineering, robotics, and mission teams to integrate AI systems with onboard autonomy stacks
• Conduct field trials and mission operations to validate system performance under real-world constraints

Staff Software Engineer – Agent Harnessing

Senior AI Researcher

Senior AI Engineer