Senior AI Platform Engineer
Listed on 2026-09-03
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IT/Tech
Cybersecurity, AI Engineer (Applied/Software), Cloud Computing: Infrastructure & Operations
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 C5
ISR Center. In this role, you will lead the technical strategy for building and accrediting a secure agentic AI platform within AWS Gov Cloud (IL5). You will combine deep cloud and platform engineering expertise with DoD security accreditation, RMF, ATO/cATO, and Dev Sec Ops 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.
Primary Responsibilities:
- 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 Gov Cloud 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 Cloud Formation.
- 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.
Required Qualifications:
- 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, Dev Ops, or MLOps engineering.
- U.S. citizenship with active Top 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.
Preferred Qualifications:
- Active TS/SCI clearance.
- Experience supporting national security, defense, or DoD environments.
- Direct experience with continuous ATO (cATO), continuous monitoring, and pipeline-based security evidence.
- Experience with Platform One, Iron Bank, or Big Bang.
- Experience with AWS Bedrock, Bedrock Agent Core, Sage Maker, or similar managed AI/ML services.
- Experience securing or accrediting systems involving LLMs, autonomous decision logic, agentic AI, or dynamic service interactions.
- Experience with cybersecurity operations, security engineering, or DoD cyber environments.
- DoD 8570 IAT Level II certification or equivalent.
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