Lead AI Solution Architect

Peraton Overview

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can’t be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we’re keeping people around the world safe and secure.

Responsibilities

About the Role

Peraton is seeking an experienced AI Solution Architect to design and lead enterprise AI/ML architectures in a secure, mission-focused environment. This individual will translate emerging artificial intelligence capabilities and organizational requirements into scalable, production-ready solutions supporting large-scale mission applications.

The ideal candidate brings deep expertise across large language models (LLMs), generative AI, agentic AI, GPU infrastructure, and MLOps, with the ability to architect solutions from initial concept and prototyping through enterprise deployment and operational sustainment. This role will provide technical leadership across data science, platform engineering, cybersecurity, infrastructure, and mission teams to ensure AI/ML solutions meet performance, security, scalability, and operational requirements.

Key Responsibilities

AI/ML Architecture & Solution Design

• Design enterprise AI/ML architectures encompassing model selection, inference infrastructure, training pipelines, MLOps, and mission application integration.

• Architect and deploy LLM, generative AI, Retrieval-Augmented Generation (RAG), and agentic AI solutions.

• Lead AI/ML solutions through the full lifecycle, from prototyping and experimentation to production deployment at enterprise scale.

• Design AI/ML architectures capable of operating in classified, disconnected, and air-gapped environments.

• Evaluate emerging AI technologies and translate new capabilities into practical, production-ready solutions.

AI/ML Infrastructure & MLOps

• Design scalable GPU infrastructure leveraging NVIDIA A100/H100 or comparable GPU platforms.

• Architect model-serving and inference environments using technologies such as vLLM, TensorRT, and Triton.

• Design and implement MLOps pipelines using MLflow, Kubeflow, or comparable platforms.

• Support containerized AI/ML environments and integration with enterprise infrastructure and platforms.

• Optimize AI/ML architectures for performance, scalability, resource utilization, cost, and operational efficiency.

AI Governance, Security & Responsible AI

• Develop secure and responsible approaches to AI deployment, governance, evaluation, and lifecycle management.

• Apply AI risk management and governance principles, including NIST AI Risk Management Framework (AI RMF).

• Address security, authorization, and operational requirements associated with deploying AI/ML capabilities in classified environments.

• Develop architectures and operational approaches supporting human-in-the-loop and human-on-the-loop AI capabilities.

Technology Strategy & Technical Leadership

• Evaluate commercial, government, and open-source AI/ML technologies to identify emerging capabilities and maintain an innovation roadmap.

• Serve as a technical liaison across data science, platform engineering, cybersecurity, infrastructure, and mission teams.

• Communicate complex AI/ML concepts, architecture decisions, and technical recommendations to both technical and non-technical stakeholders.

• Provide technical leadership and architectural guidance while balancing innovation, mission requirements, security, scalability, and production readiness.

Location: This position is fully onsite in Chantilly, VA.

Qualifications

Minimum of 12 years with BS/BA; Minimum of 10 years with MS/MA

Basic Qualifications

• 12+ years of experience and a Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related technical discipline. An additional 4 years of experience may be considered in lieu of a degree. 

• 10+ years of relevant experience in AI/ML architecture, engineering, or technical leadership.

• Demonstrated experience designing and deploying production AI/ML architectures at enterprise scale.

• Strong experience with LLM architecture, transformer models, Retrieval-Augmented Generation (RAG), and generative AI.

• Experience with model fine-tuning techniques, including LoRA, QLoRA, and/or Parameter-Efficient Fine-Tuning (PEFT).

• Experience designing and implementing GPU architectures leveraging NVIDIA A100/H100 or comparable platforms.

• Experience with model-serving and inference technologies, including vLLM, TensorRT, and/or Triton.

• Experience designing MLOps pipelines using MLflow, Kubeflow, or comparable platforms.

• Experience with agentic AI frameworks, such as LangChain, LangGraph, or AutoGen.

• Demonstrated experience designing or deploying AI/ML solutions within classified, disconnected, or air-gapped environments.

• Ability to address AI governance, security, risk management, and responsible AI requirements.

• Active TS/SCI clearance with Polygraph.

Preferred Qualifications

• Experience deploying AI/ML workloads using Kubernetes and/or OpenShift.

• Experience with vector databases, including Milvus, Weaviate, or pgvector.

• Experience with data engineering technologies such as Apache Spark and/or Airflow.

• Experience with model evaluation frameworks, including HELM or lm-eval.

• Experience applying the NIST AI Risk Management Framework (AI RMF).

• Experience with ONNX optimization for edge or distributed computing environments.

• Experience with GPU capacity planning, resource optimization, and cost modeling.

• Experience working with large-scale datasets, including video data.

• Experience operating AI/ML solutions across multiple security domains or classification environments.

Target Salary Range

$146,000 - $234,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
Benefits Statement

Peraton offers eligible employees a variety of benefits including medical, dental, vision, life, health savings account, short/long term disability, EAP, parental leave, 401(k), paid time off (PTO) for vacation, and company paid holidays. A full listing of available benefits can be viewed at https://www.careers.peraton.com/benefits.

Application Statements


EEO

EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.