AI Platform and DevSecOps Engineer

Johns Hopkins Applied Physics Laboratory (APL) seeks an AI Platform and DevSecOps Engineer to build and secure mission-critical AI infrastructure for Defense & Aerospace within our IT & Cybersecurity organization. You will design cloud-native, containerized AI/ML platforms, implement secure CI/CD pipelines, and embed DevSecOps practices across the model and software lifecycle. Partnering with cybersecurity, data science, and mission experts, you’ll harden systems to DoD and NIST standards while enabling rapid innovation. At APL, you’ll work in a collaborative, research-driven culture with strong support for growth, advanced degrees, and impactful, mission-focused careers., * Design, deploy, and secure AI/ML platforms to support Defense & Aerospace missions

• Implement Dev
• Sec
• Ops pipelines (CI/CD) for secure software and ML model delivery
• Automate cloud-native infrastructure using infrastructure-as-code and container orchestration
• Integrate security scanning, compliance, and monitoring across the AI development lifecycle
• Collaborate with cybersecurity, data science, and mission teams to productionize models
• Harden systems to meet Do
• D, NIST, and zero-trust security requirements
• Optimize performance, reliability, and scalability of AI workloads in hybrid environments
• Develop documentation, runbooks, and knowledge sharing for platform users
• Troubleshoot complex system, networking, and security issues in production
• Contribute to innovation, proofs-of-concept, and technology evaluations

• Dev
• Sec
• Ops tooling (Git
• Lab CI, Git
• Hub Actions, Jenkins, or similar)
• Kubernetes and containerization (Docker)
• Cloud platforms (AWS, Azure, or similar, including Gov/secure clouds)
• Infrastructure as Code (Terraform, Ansible, or similar)
• AI/ML platforms (Kubeflow, MLflow, Sage
• Maker, or similar)
• Secure software development and CI/CD security scanning
• Linux administration and shell scripting
• Networking, zero-trust, and NIST/Do
• D security frameworks
• Python or similar programming language
• Monitoring, logging, and observability (Prometheus, Grafana, ELK, etc.)