AI Platform Engineer

VAE, Inc.; Virginia (MN); On-site; USD 175,000 - 225,000; Full time

Job summary

VAE, Inc. seeks an AI Platform Engineer to own the technical accreditation strategy and cloud runtime for the C5ISR program's agentic AI platform.

This role sits at the intersection of platform engineering, DevSecOps, and security accreditation, serving as the primary interface to security engineering and authorization staff. The ideal candidate has deep AWS GovCloud and Kubernetes experience with hands-on ATO/cATO lineage.

Qualifications

• Bachelor's or Master's degree in CS/EE/Data Science or related field.
• 8+ years of hands-on cloud/platform/DevOps or MLOps engineering.
• Active Secret clearance with ability to obtain Top Secret clearance.
• DOD 8570 certification required.
• Experience taking a system through formal security accreditation and interfacing with security stakeholders.
• Hands-on DoD/federal accredited cloud environment (IL4/IL5, FedRAMP).
• Proficiency in Python and at least one IaC tech.
• Hands-on experience with AWS, Docker, and Kubernetes in deployments.
• Experience building and maintaining CI/CD pipelines.
• Understanding of ML/LLM serving, scaling, securing, and monitoring.

Responsibilities

• Own the technical accreditation strategy for the program's agentic AI platform, including control approach for model and behavior.
• Author and maintain artifacts supporting ATO and cATO packages (POA&M, architecture and data flow docs).
• Interface with security engineering, ISSO/ISSM, and authorizing staff to support authorization decisions.
• Design, build, and operate the AWS GovCloud cloud runtime for agentic AI workloads (IL5) with Kubernetes.
• Implement and maintain CI/CD pipelines and infrastructure as code (Terraform, CloudFormation) including container hardening.
• Integrate Amazon Bedrock and other model endpoints; manage IAM, quotas, and network boundaries.
• Instrument traffic for logging, tracing, cost attribution, and audit for observability.
• Apply MLOps best practices: model/versioning, deployment gating, monitoring, rollback.
• Mentor engineers on accreditable design patterns and secure development practices.
• Develop and execute the platform technical roadmap aligned to program goals.

Skills

AWS GovCloud

Kubernetes

Terraform

CloudFormation

CI/CD pipelines

Python

DoD IL4/IL5

Security accreditation

Active Secret clearance

8570 certification

Platform One

Bedrock

SageMaker

Education

Bachelor's or Master's degree in Computer Science, Electrical Engineering, Data Science, Mathematics, or a related field

Tools

Terraform

CloudFormation

Docker

Kubernetes

Platform One

Bedrock

SageMaker

Job description

Share this job as a link in your status update to LinkedIn.

OVERVIEW

VAE, Inc. is a full service IT Infrastructure Solutions Company focused on building, securing and supporting our clients’ mission critical enterprises. We provide a distinctive array of design, integration and implementation services as well as fully managed service offerings. VAE is at the forefront of leveraging multi-tenant capable technologies and shared IT services to create secure, reliable and cost-effective end-to-end services and solutions. We deliver exceptional infrastructure solutions with extremely talented employees using a client-focused partnering approach.

Job Type

Full-time

Location

VA US (Primary)

Job Description

VAE, Inc. is seeking an AI Platform Engineer to own the technical accreditation strategy and cloud runtime for the C5ISR program's agentic AI platform. This role sits at the intersection of platform engineering, DevSecOps, and security accreditation, serving as the primary technical interface to security engineering, ISSO/ISSM, and authorizing official staff. The ideal candidate combines deep AWS GovCloud/Kubernetes platform experience with hands-on experience carrying a system through formal ATO or cATO accreditation.

Key Responsibilities

• Own the technical accreditation strategy for the program's agentic AI platform, including the control approach for model, tool, and agent-to-agent behavior.
• Author and maintain the technical artifacts supporting the ATO and cATO package: control narratives, architecture and data flow documentation, boundary definitions, POA&M inputs, and scan evidence.
• Serve as the primary technical interface to security engineering, ISSO/ISSM, and authorizing official staff, translating agentic AI architecture into terms that support an authorization decision.
• Design, build, and operate the cloud runtime that agentic AI workloads deploy onto in AWS GovCloud at IL5, including Kubernetes deployment, scaling, observability, and failure recovery.
• Implement and maintain CI/CD pipelines and infrastructure as code (Terraform, CloudFormation, or comparable) using Platform One and DevSecOps tooling, including container hardening and image accreditation.
• Integrate Amazon Bedrock and other authorized model endpoints, managing IAM, service quotas, network boundaries, and data flow controls.
• Instrument agent and tool traffic for logging, tracing, cost attribution, and audit so that automated activity remains observable, attributable, and distinguishable from anomalous behavior.
• Apply best practices for MLOps, including model and prompt versioning, deployment gating, monitoring, and rollback.
• Mentor engineers on accreditable design patterns and secure development practices.
• Develop and execute the platform technical roadmap tied to program and business objectives.

Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Data Science, Mathematics, or a related field.
• 8+ years of hands-on experience in cloud, platform, DevOps, or MLOps engineering.
• Active Secret clearance, with the ability to obtain and maintain a Top Secret clearance.
• An active DOD 8570 certification required
• Demonstrated experience taking a system through a formal security accreditation, including authoring or substantially contributing to control documentation and interfacing directly with security and authorization stakeholders.
• Hands-on experience operating in a DoD or federal accredited cloud environment (IL4/IL5, FedRAMP Moderate/High, or comparable).
• Proficiency in Python and in at least one infrastructure as code technology.
• Hands-on experience with AWS, container technologies (Docker), and Kubernetes in operational deployments.
• Demonstrated experience building and maintaining CI/CD pipelines.
• Working understanding of how ML and LLM workloads are served, scaled, secured, and monitored.
• Strong collaboration and communication skills, including the ability to defend a technical position to security stakeholders.

Preferred Qualifications

• Experience working in national security or defense environments.
• Direct experience with continuous ATO (cATO) and the associated continuous monitoring and pipeline evidence expectations.
• Hands-on experience with Platform One, Iron Bank, or Big Bang.
• Experience with AWS Bedrock, Bedrock AgentCore, SageMaker, or comparable managed model services.
• Experience accrediting or securing systems that use LLMs, autonomous decision logic, or dynamic service discovery.
• Some exposure to cyber security work (DoD cyber operations, SOC, or security engineering).

Clearance Level

Secret

Certifications

8570

Salary Range

$175,000-$225,000

VAE, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.