AI Platform and DevSecOps Engineer

Johns Hopkins Applied Physics Laboratory•Laurel, MD

177d•Onsite

About The Position

This role is for an AI Platform and DevSecOps Engineer at APL, working at the forefront of operationalizing artificial intelligence in national security environments. The engineer will bridge the gap between AI development and real-world deployment, ensuring that advanced capabilities, including large language models and supporting services, are delivered securely, reliably, and at scale to mission environments. Working within the Advanced Mission Modeling and AI Group (JAM) in the National Security Analysis Department (NSAD), the engineer will play a critical role in ensuring that AI capabilities are successfully fielded and maintained across DoD and Combatant Command infrastructures.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering or a closely related technical field.
At least three years of relevant experience deploying software across Windows and Linux.
Experience with containerization technologies (Docker, Podman) and orchestration (Kubernetes).
Familiarity with CI/CD pipelines and DevSecOps practices.
Experience with vulnerability scanning and remediation.
Proficiency in Bash, or similar scripting languages.
Strong problem-solving skills in constrained environments.
Able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a TS/SCI level clearance.
U.S. citizenship.

Nice To Haves

Experience deploying to classified or air-gapped environments.
Familiarity with DoD DevSecOps processes.
Experience supporting AI/ML or LLM-based systems.
Knowledge of container security hardening and STIGs.
Experience with multi-architecture builds.
Experience with Kubernetes in restricted environments.

Responsibilities

Develop, maintain, and continuously update a secure library of containerized software and supporting stacks.
Implement automated pipelines for container builds, testing, and validation, ensuring compatibility across multiple operating systems and architectures.
Design, deploy, and maintain Kubernetes-based infrastructure.
Maintain well-documented, reproducible deployment configurations.
Optimize performance and reliability across constrained environments.
Develop processes to continuously scan containers and dependencies for vulnerabilities and remediate findings.
Ensure compliance with evolving STIG requirements and security controls.
Integrate security best practices into CI/CD pipelines.
Navigate deployments across DoD and IC systems.
Adapt deployment strategies to meet ATO and accreditation constraints.
Troubleshoot environment-specific deployment issues.