AI Architect (AI Security + Federal)

Jobot · Washington, DC · 2 mo ago

RemoteRemoteDesign$200k–$275k/yrFull-time

Job Details

This Jobot Job is hosted by: Craig Rosecrans

What You'll Do

Lead Federal Technical Engagements: Partner with federal Account Directors to lead technical strategy across complex government opportunities. Conduct discovery with mission owners, AI/ML engineers, security teams, architects, and executive stakeholders. Understand customers' AI initiatives, architectures, data pipelines, infrastructure, security requirements, and compliance constraints. Translate loosely defined mission challenges into clearly scoped technical evaluations and proof-of-value engagements. Establish measurable success criteria, timelines, technical requirements, and exit conditions. Serve as a trusted technical advisor and provide candid guidance around where the platform is—and is not—the right solution.
Architect & Deploy Real Solutions: Architect and deploy an enterprise AI security platform across both connected SaaS and fully disconnected/air-gapped environments. Package and transfer container images, Helm charts, dependencies, and supporting artifacts into environments with limited or no internet connectivity. Deploy and administer Kubernetes-based environments utilizing technologies such as: Kubernetes Docker Helm Private container registries OpenShift VMware / Proxmox AWS, including government and restricted environments Troubleshoot deployment, networking, integration, and infrastructure issues during customer evaluations and initial implementations. Work directly with SDKs and APIs to build meaningful integrations into customer environments.
Build AI Demonstrations & Proofs of Concept: Develop mission-focused AI applications and technical demonstrations involving: Large Language Models Agentic AI Computer Vision Model inference Retrieval/RAG architectures AI/ML pipelines Demonstrate how AI systems can be attacked, compromised, or manipulated—and how those systems can be protected. Integrate AI security capabilities throughout the ML lifecycle, including model scanning, CI/CD pipelines, application security, runtime detection, and response. Build credible demonstrations that resonate with engineers and mission owners rather than relying on canned sales demos.
Advise on AI Security: Help federal customers understand how to secure: AI/ML models LLM-powered applications AI agents Data and inference pipelines Model supply chains AI infrastructure Production AI workloads Apply established security concepts and frameworks including: MITRE ATLAS OWASP Top 10 for LLM Applications NIST AI Risk Management Framework Adversarial machine learning concepts and attack methodologies Communicate & Influence: Deliver live technical demonstrations, architecture sessions, whiteboard discussions, and executive briefings. Present effectively to audiences ranging from ML engineers and data scientists to cybersecurity leaders and senior executives. Create technical evaluation reports, reference architectures, deployment documentation, and integration guides. Represent the organization at federal engagements, conferences, webinars, and industry events. Translate lessons learned in the field into reusable demonstrations, technical enablement, and feedback for Product, Research, and Engineering.

What We're Looking For

We are looking for a highly technical, customer-facing architect who has actually worked inside federal environments and understands the realities of deploying sophisticated technology into government infrastructure. Ideal candidates will bring:
5+ years of experience in Solutions Architecture, Solutions Engineering, Applied AI Engineering, ML Engineering, or a similar customer-facing technical role.
Direct experience supporting federal customers across the Intelligence Community, DoD, DHS, or civilian agencies.
Experience operating within federal missions—not simply selling technology into federal accounts.
Strong hands-on Python development skills.
Practical experience building and integrating modern AI/ML systems.
Experience with technologies and concepts such as: PyTorch Hugging Face ONNX LLM APIs Model inference RAG Agentic AI architectures AI/ML pipelines Strong hands-on experience with Docker, Kubernetes, and Helm.
Experience deploying applications into restricted, disconnected, or air-gapped environments.
Understanding of MLOps, CI/CD, and the lifecycle of models from development through production.
Working knowledge of cybersecurity and AI security concepts.
Strong technical presentation and communication skills.
Ability to take an ambiguous customer problem and independently turn it into an executable technical plan.
Ability and willingness to travel for customer engagements and industry events.
Additional experience in any of the following areas would be highly desirable: Active Top Secret or higher-level security clearance. Supporting AI/ML programs in classified environments. Securing production AI or machine-learning systems. AI/LLM red teaming or adversarial machine learning. AI security or AI evaluation tooling. Model formats and AI supply-chain security, including: ONNX SafeTensors GGUF Pickle-based serialization AWS GovCloud or other government cloud environments. OpenShift and private Kubernetes environments. Federal cybersecurity or compliance frameworks. Certifications such as Kubernetes, AWS, Azure, CISSP, or Security+. Public technical work including GitHub repositories, Hugging Face projects, conference presentations, open-source contributions, or technical writing.

Why Join Us?

You'll join a well-funded, rapidly scaling company building technology in one of the most important emerging areas of cybersecurity: protecting AI systems themselves.
The company has recently completed a significant new funding round and is continuing to expand its engineering, product, and federal organizations.
The opportunity offers: Fully remote work within the United States Significant exposure to cutting-edge AI and cybersecurity technology Direct involvement with important federal AI initiatives High technical autonomy and ownership Opportunity to work closely with Product, Research, Engineering, and customers Flexible paid time off Company holidays Home-office and connectivity support Dedicated learning and development funding for training, certifications, conferences, and industry events.

Qualifications

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