AI Solutions Architect- Federal

HiddenLayer; United States; Remote; USD 150,000 - 230,000; Full time

Benefits offered by this job

Home office setup stipend

Equipment refresh program

Internet & phone allowance

Health plan options

Paid holidays

Job summary

HiddenLayer is seeking an AI Solutions Architect to lead pre‑sales technical engagements for federal agencies. You will guide discovery, architect deployments in SaaS and airgapped environments, and drive value from initial discovery to win.

The role is remote within the United States, with DC Metro preference and TS clearance strongly preferred. Responsibilities include leading workshops, mapping missions, detailing security requirements, and delivering compelling demos.

Qualifications

• 5+ years in solutions architecture with direct federal customer support.
• Proficiency in Python and modern AI/ML tooling.
• Experience deploying Kubernetes across cloud and on‑prem.
• Strong written and verbal communication, executive presentations.
• Willingness to travel for customer engagements and events.

Responsibilities

• Lead discovery workshops to map missions, AI initiatives, architectures, data pipelines, and security needs.
• Translate problems into scoped proof-of-value engagements with success criteria.
• Architect and deploy the platform in SaaS and airgapped environments.
• Stand up Kubernetes deployments using Docker, Helm, and private registries across diverse environments.
• Build demos and proof‑of‑concept AI apps integrated with platform SDKs and APIs.
• Advise customers on securing models and data pipelines per MITRE ATLAS, OWASP LLM, and NIST RMF.
• Deliver live demos, write evaluation reports, and convert field learnings into reusable demos.

Skills

Python

AI/ML tooling

Kubernetes

Communication

Federal engagements

Tools

Docker

Helm

AWS GovCloud

OpenShift

Job description

Role overview

AI Solutions Architect serving as the pre-sales technical lead for federal pursuits across the Intelligence Community, DoD/DoW, DHS, and civilian agencies. The role carries opportunities from initial discovery through proof of value and technical win, architecting deployments in connected SaaS and fully airgapped environments. It is remote within the United States, with DC Metro preferred and an active Top Secret clearance (or TS eligibility) strongly preferred.

Responsibilities

• Lead discovery workshops to map customer missions, AI initiatives, architectures, data pipelines, and security and compliance needs.
• Translate loosely defined mission problems into scoped proof-of-value engagements with clear success criteria and exit conditions.
• Architect and deploy the platform in SaaS and airgapped environments, including container images, Helm charts, and offline transfer artifacts.
• Stand up and administer Kubernetes-based deployments using Docker, Helm, and private registries across AWS GovCloud, disconnected regions, and on-premises platforms like VMware, Proxmox, and OpenShift.
• Build mission-focused demos and proof-of-concept AI applications spanning computer vision, LLM, and agentic workloads, integrated end-to-end with platform SDKs and APIs.
• Advise customers on securing models, AI applications, and data pipelines against frameworks such as MITRE ATLAS, the OWASP Top 10 for LLM Applications, and the NIST AI RMF.
• Deliver live demos, write evaluation reports and reference architectures, and convert field learnings into reusable demos and product feedback.

Requirements

• 5+ years in solutions architecture, solutions engineering, or applied AI engineering with direct federal customer support across IC, DoD/DoW, DHS, or civilian agencies.
• Hands‑on fluency with Python and modern AI/ML tooling.
• Demonstrated ability to deploy and operate Kubernetes-based systems across cloud and on-premises environments.
• Strong written and verbal communication skills, including executive-level presentations.
• Ability to travel as needed for customer engagements and industry events.
• Active Top Secret clearance or TS eligibility strongly preferred.

Nice to have

• Experience securing AI/ML systems in production or supporting AI programs in classified environments.
• Familiarity with model file formats and AI supply chain concerns, including ONNX, SafeTensors, GGUF, and pickle‑based serialization.
• Red‑teaming experience with LLM applications or AI security and evaluation tooling.
• Relevant certifications such as Kubernetes, AWS, Azure, CISSP, or Security+, or prior work under federal compliance regimes.
• Public work such as GitHub repositories, conference talks, or technical writing.

Benefits and work setup

• Fully remote global team with periodic in-person gatherings.
• Home office setup stipend, annual equipment refresh, and monthly internet and phone allowance.
• Multiple fully subsidized health plan options, plus vision, dental, and 401(k) coverage.
• Unlimited flexible time off plus 15 paid company holidays.
• Dedicated learning and development budget for training, conferences, certifications, and events.