Principal Agentic AI Engineer; T5

Overview Working across the globe, V2X builds smart solutions designed to integrate physical and digital infrastructure from base to battlefield. We bring 120 years of successful mission support to improve security, streamline logistics, and enhance readiness. Aligned around a shared purpose, our $3.9B company and 16,000 people work alongside our clients, here and abroad, to tackle their most complex challenges with integrity, respect, responsibility, and professionalism.

Responsibilities V2X is seeking an accomplished Principal Agentic AI Engineer (T05) to join our Software Department in Indianapolis, Indiana.

The ideal candidate embraces modern AI‑driven development processes and engineering techniques that accelerate capability delivery, improve mission effectiveness, and enhance team productivity. They have experience designing, building, and integrating advanced agentic systems, including autonomous decision-support frameworks, intelligent mission planning tools, adaptive control systems, multi‑sensor fusion pipelines, and AI-enabled situational awareness technologies. We are looking for engineers who enjoy tackling complex, emerging challenges and have a passion for supporting our DoD customers and international partners.

The Principal Agentic AI Engineer provides technical leadership across the full system development lifecycle, from conceptual architecture and requirements definition through model development, agentic workflow design, simulation, verification, validation, and final deployment. The role requires strong communication skills, collaborative problem‑solving, and the ability to translate complex mission needs into practical, advanced AI solutions.

Qualifications Education Requirements:

• Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related STEM field.

Required Skills

• Must be a U.S. Citizen with the ability to obtain a DoD Secret Clearance
• At least 12 years of related engineering experience in systems, software, or hardware engineering.
• Deep expertise in designing and implementing agentic AI architectures and autonomous decision‑making systems
• Strong proficiency in modern machine learning techniques, including model development, evaluation, and optimization
• Experience building reasoning, planning, and multi‑step workflow automation using AI agents
• Ability to design and evaluate autonomous behaviors, control logic, and adaptive system responses
• Skilled in developing scalable AI pipelines, simulation frameworks, and experimentation environments
• Strong understanding of safety, reliability, and assurance considerations for AI‑driven systems
• Proficiency with Python and modern AI/ML frameworks (e.g., PyTorch, Tensor Flow, JAX, Lang Chain‑style orchestration)
• Ability to translate mission objectives and operational constraints into technical system requirements
• Experience with data engineering practices including preprocessing, feature extraction, and sensor/mission data handling
• Strong analytical problem‑solving skills and ability to lead complex technical efforts
• Excellent communication skills for describing AI system behavior, trade‑offs, and technical decisions to diverse stakeholders
• Familiarity with distributed systems, cloud platforms, or edge compute environments for model deployment
• Ability to guide junior engineers, provide technical mentorship, and set engineering direction

Desired Skills

• Experience developing multi-agent systems or orchestrating large‑scale agentic workflows
• Background in autonomous systems engineering, robotics, or intelligent control
• Familiarity with reinforcement learning, planning algorithms, or neuro‑symbolic techniques
• Knowledge of mission data pipelines, sensor fusion, or real‑time decision‑support systems
• Experience with high‑assurance or safety‑critical AI development practices Proficiency in designing AI evaluation frameworks, synthetic data generation, or simulation‑based testing
• Understanding of human‑machine teaming concepts and explainable AI practices
• Experience deploying AI models on edge compute platforms or constrained environments
• Familiarity with model governance, ML Ops, or lifecycle management tools
• Prior DoD,…