Artificial Intelligence Engineer

Principal AI Systems Architect – Autonomous Defense & Secure Intelligence Systems

Position Summary

The Principal AI Systems Architect leads the design, development, and deployment of mission-critical artificial intelligence systems operating in contested, security-sensitive, and edge environments. This role bridges advanced AI research with operational capability, architecting autonomous systems that integrate computer vision, reinforcement learning, secure AI infrastructure, multi-sensor fusion, and distributed decision-making. The ideal candidate combines deep software engineering expertise with systems thinking, enabling the rapid transition of emerging technologies from concept to field-ready solutions.

Key Responsibilities

• Architect secure AI platforms for classified and mission-critical environments.
• Lead the development of autonomous perception, planning, and decision-making systems for robotic and unmanned platforms.
• Design scalable AI infrastructure supporting local, edge, and cloud inference across multiple security domains.
• Drive research and implementation of reinforcement learning, computer vision, LLMs, agentic AI, and multi-agent systems.
• Develop safety-critical AI architectures emphasizing explainability, verification, human oversight, and operational resilience.
• Translate operational challenges into deployable software and hardware solutions.
• Mentor engineering teams while establishing technical standards and AI development best practices.
• Collaborate with government, defense, and commercial stakeholders to mature emerging technologies into production capabilities.
• Lead innovation efforts including patent development, technical strategy, and technology roadmaps.

Desired Qualifications

• Expertise in Python, Rust, TypeScript, PyTorch, and modern AI frameworks.
• Experience with edge AI, embedded systems, computer vision, reinforcement learning, and autonomous robotics.
• Strong background in distributed systems, secure software architecture, and AI infrastructure.
• Experience designing AI for regulated or high-assurance environments.
• Proven record of innovation through patents, research, or open-source contributions.
• Ability to bridge research, engineering, and operational execution.
• Active or previously held TS/SCI clearance preferred.

Ideal Candidate Profile

• The successful candidate is an AI-enabled systems engineer who combines software architecture, machine learning, autonomous systems, and operational domain expertise to solve complex real-world problems. They are equally comfortable developing novel AI algorithms, designing secure production infrastructure, mentoring engineering teams, and translating mission requirements into scalable technical solutions. Their work extends beyond software development to include technical strategy, invention, and the creation of next-generation intelligent systems.