Senior AI Platform Engineer

Leidos is seeking a Senior AI Platform Engineer to join our DCSB Artificial Intelligence & Agent Development team supporting the U.S. Army C5ISR Center. In this role, you will lead the technical strategy for building and accrediting a secure agentic AI platform within AWS GovCloud (IL5). You will combine deep cloud and platform engineering expertise with DoD security accreditation, RMF, ATO/cATO, and DevSecOps practices to ensure AI capabilities can be securely deployed into operational environments. This is not a traditional AI/ML development position. Your primary challenge will be creating a secure, observable, and accreditable platform on which agentic AI capabilities can operate. You will serve as a key technical interface between platform engineering, security engineering, ISSO/ISSM personnel, and Authorizing Official (AO) stakeholders. You will also help establish secure engineering patterns so accreditation is built into the platform from the beginning rather than addressed after development. Location: Remote, however must be within commuting distance of Adelphi, MD to report on site as needed. Clearance: U.S. citizenship with an active Top Secret Clearance and ability to obtain SCI.

Lead the technical accreditation strategy for the agentic AI platform, including security controls for models, tools, and agent-to-agent interactions. Develop and maintain technical artifacts supporting ATO and continuous ATO (cATO), including control narratives, architecture diagrams, data flows, boundary definitions, POA&M inputs, and security scan evidence. Partner with security engineering, ISSO/ISSM personnel, and AO stakeholders to translate complex AI and cloud architectures into evidence supporting authorization decisions. Design, build, and operate a secure AWS GovCloud IL5 platform supporting agentic AI workloads. Deploy and manage containerized workloads using Kubernetes and Docker, including scaling, observability, resiliency, and failure recovery. Build and maintain CI/CD pipelines and Infrastructure as Code (IaC) using Platform One and technologies such as Terraform or CloudFormation. Support container hardening, image accreditation, and secure software delivery practices. Integrate Amazon Bedrock and other authorized AI/ML services, managing IAM, network boundaries, service quotas, and data flow controls. Implement logging, tracing, monitoring, auditability, and cost attribution for agent and tool activity. Apply MLOps practices including model and prompt versioning, deployment gating, monitoring, and rollback. Mentor engineers on secure, accreditable architecture and development practices. Develop and execute the platform technical roadmap aligned with program and mission objectives.

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field. 8+ years of hands-on experience in cloud, platform, DevOps, or MLOps engineering. U.S. citizenship with active Tope Secret clearance with the ability to obtain and maintain SCI. Demonstrated experience supporting a system through formal security accreditation/RMF, including substantial contributions to security control documentation and direct interaction with security or authorization stakeholders. Experience operating within a DoD or federal accredited cloud environment, such as IL4/IL5, FedRAMP Moderate/High, or comparable. Hands-on experience with AWS, Kubernetes, Docker, and Infrastructure as Code. Experience designing, building, and maintaining CI/CD pipelines. Proficiency in Python. Working knowledge of how ML/LLM workloads are deployed, scaled, secured, and monitored. Strong communication skills with the ability to explain and defend technical architecture and security decisions.

Active TS/SCI clearance. Experience supporting national security, defense, or DoD environments. Direct experience with continuous ATO (cATO), continuous