Lead AI Solution Architect

Peraton • Chantilly, VA

20h • $146,000 - $234,000 • Onsite

About The Position

Peraton is seeking an experienced AI Solution Architect to design and lead enterprise AI/ML architectures in a secure, mission-focused environment. The role translates emerging artificial intelligence capabilities and organizational requirements into scalable, production-ready solutions for large-scale mission applications. The architect provides technical leadership across data science, platform engineering, cybersecurity, infrastructure, and mission teams to ensure AI/ML solutions meet performance, security, scalability, and operational requirements.

The position covers the full solution lifecycle, from concept and prototyping through enterprise deployment and operational sustainment. It includes architecture for LLMs, generative AI, RAG, agentic AI, GPU infrastructure, model serving, inference, MLOps, governance, and secure deployment in classified, disconnected, or air-gapped environments. The role is fully onsite in Chantilly, Virginia.

Requirements

• 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 using 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 in classified, disconnected, or air-gapped environments.
• Ability to address AI governance, security, risk management, and responsible AI requirements.
• Active TS/SCI clearance with Polygraph.

Nice To Haves

• 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.

Responsibilities

• Design enterprise AI/ML architectures covering 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 prototyping and experimentation to production deployment at enterprise scale.
• Design AI/ML architectures for classified, disconnected, and air-gapped environments.
• Evaluate emerging AI technologies and translate new capabilities into practical, production-ready solutions.
• Design scalable GPU infrastructure using NVIDIA A100/H100 or comparable 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 their integration with enterprise infrastructure and platforms.
• Optimize AI/ML architectures for performance, scalability, resource utilization, cost, and operational efficiency.
• Develop secure and responsible approaches to AI deployment, governance, evaluation, and lifecycle management.
• Apply AI risk management and governance principles, including the NIST AI Risk Management Framework.
• Address security, authorization, and operational requirements for AI/ML capabilities in classified environments.
• Develop architectures and operational approaches supporting human-in-the-loop and human-on-the-loop AI capabilities.
• Evaluate commercial, government, and open-source AI/ML technologies and maintain an innovation roadmap.
• Serve as a technical liaison across data science, platform engineering, cybersecurity, infrastructure, and mission teams.
• Communicate AI/ML concepts, architecture decisions, and technical recommendations to technical and non-technical stakeholders.
• Provide technical leadership and architectural guidance while balancing innovation, mission requirements, security, scalability, and production readiness.

Benefits

• Medical benefits
• Dental insurance
• Vision insurance
• Life insurance
• Health savings account
• Short- and long-term disability
• Employee assistance program (EAP)
• Parental leave
• 401(k)
• Paid time off for vacation
• Company-paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Senior