Job Requirements
Remote
Secret Polygraph not specified
Early Career (2+ yrs experience)
Salary not specified
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Job Description
AI Platform Engineer
Position Overview
We are 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.
Required 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
• Active Top Secret clearance.
• 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).
Position Overview
We are 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.
Required 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
• Active Top Secret clearance.
• 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).
group id: 10471702