AI Architect (AI Security + Federal)

This Jobot Job is hosted by: Craig Rosecrans
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Salary: $200,000 - $275,000 per year

A bit about us:

We are partnering with a rapidly growing, venture-backed technology company operating at the intersection of Artificial Intelligence and cybersecurity to hire an AI Solutions Architect focused on Federal customers.

This is not a traditional Solutions Architect position where you simply deliver presentations and hand opportunities back to Engineering.

We are looking for someone who can architect, build, deploy, demonstrate, and troubleshoot real AI solutions while working directly with mission owners across the Intelligence Community, Department of Defense, DHS, and civilian federal agencies.

You will serve as the technical lead throughout the customer journey-from initial discovery and architecture discussions through proof-of-value, deployment, integration, and technical win.

The right person will be equally comfortable writing Python, deploying Kubernetes into an air-gapped environment, building an AI proof of concept, whiteboarding an architecture, and presenting the solution to senior government stakeholders.

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

If you're a deeply technical Solutions Architect who understands Federal missions, AI/ML, cloud-native infrastructure, and security-and you want to help solve the emerging challenge of securing AI systems-we'd love to speak with you.

Job Details

**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.

Especially Valuable Experience:
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.

The Type of Person Who Will Thrive Here:
This organization moves quickly and operates much more like a high-growth technology company than a traditional government contractor.

We're looking for someone who enjoys solving problems without a perfectly defined playbook.

You should be someone who can walk into an ambiguous federal mission problem, ask the right questions, architect a solution, stand up the environment, write the integration, demonstrate it live, troubleshoot what breaks, and explain the outcome to both engineers and executives.

Intellectual curiosity is especially important. The strongest candidates are typically people who are constantly experimenting-building side projects, maintaining home labs, testing new AI frameworks, contributing to open source, publishing technical content, or simply teaching themselves technologies because they want to understand how they work.

Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.

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