Platform DevOps Engineer

Gormat; Maryland; On-site; USD 180,000 - 240,000; Full time

Job summary

Gormat is seeking an experienced DevOps/platform engineer to own end-to-end infrastructure for AI deployment in a high-security, national-mission environment. You will architect and operate scalable cloud and on-prem AI platforms, implement robust CI/CD, and enforce security guardrails.

You will collaborate with AI/ML teams to optimize resource usage, maintain RMF/ATO readiness, and continuously adopt new DevOps practices to support enterprise AI delivery.

Qualifications

• Bachelor's degree with 10+ years of experience, or Master's with 8+ years.
• Active TS/SCI clearance w/ Poly.
• Advanced proficiency in DevOps principles and practices.
• Demonstrated expertise in containerization using Docker and Kubernetes.
• Proven experience in architecting and managing CI/CD pipelines.
• Extensive experience with AI model lifecycle management and maintenance.

Responsibilities

• Provide embedded operations support and rapid prototyping for AI-enabled tools.
• Design and maintain robust infrastructure for enterprise AI apps in cloud and on-prem environments.
• Develop and optimize engineering workflows for AI model deployment and maintenance.
• Architect and manage CI/CD pipelines for AI models, agents, and apps.
• Implement and manage containerization and guardrails, including identity, policy, audit/logging, and observability.
• Ensure lifecycle management, monitoring, and scaling of AI models and agents.
• Collaborate with AI/ML teams to streamline deployment and resource utilization.
• Oversee performance, security, and scalability with RMF/ATO readiness.

Skills

DevOps practices

AI lifecycle management

Security clearance

Cross-team collaboration

Education

Bachelor's degree in a relevant technical field

Master's degree in a relevant technical field

Tools

Docker

Kubernetes

Prometheus

Grafana

ELK stack

Job description

Are you an experienced DevOps/platform engineer who thrives in a fast-paced environment? Do you enjoy owning infrastructure end to end, and want to help shape how AI is deployed and delivered across a national mission? If so, you can be part of a team that supports the United States Cyber Command (USCC)!

Our team is standing up USCYBERCOM's AI Enterprise capability - the central hub that mission teams turn to when they want to move an AI solution from prototype to a secure, governed, enterprise-scale service.

What You'll Be Doing

Research, design, develop, and test operating systems-level software, compilers, and network distribution software for medical, industrial, military, communications, aerospace, business, scientific, and general computing applications. Set operational specifications and formulate and analyze software requirements. May design embedded systems software. Apply principles and techniques of computer science, engineering, and mathematical analysis.

• Provide embedded operations support, capability integration, and rapid prototyping for AI-enabled tools in support of our customer.
• Design, implement, and maintain robust infrastructure for enterprise AI applications in cloud environments (AWS, Microsoft Azure) and on-prem/air-gapped/classified environments.
• Develop and optimize engineering workflows and processes to support AI model and agent development, deployment, and maintenance.
• Architect and manage CI/CD pipelines for continuous integration and continuous delivery of AI models, agents, and applications.
• Implement and manage containerization and orchestration solutions using Docker and Kubernetes, and build and maintain control-plane guardrails - identity, policy enforcement, approvals, audit/logging, and observability.
• Ensure efficient AI model and agent lifecycle management, including versioning, monitoring, and scaling.
• Collaborate with AI/ML engineers and data scientists to streamline deployment processes and optimize resource utilization.
• Oversee system performance, security, and scalability of AI infrastructure, and support security accreditation (RMF/ATO) of AI systems.
• Continuously research and implement new DevOps tools and practices to enhance efficiency.

Required Qualifications

• Bachelor's degree in a relevant technical field with 10+ years of experience, or Master's degree in a relevant technical field with 8+ years of experience
• Active TS/SCI clearance w/ Poly
• Advanced proficiency in DevOps principles and practices
• Demonstrated expertise in containerization using Docker and Kubernetes
• Proven experience in architecting and managing CI/CD pipelines
• Extensive experience with AI model lifecycle management and maintenance

Desired Qualifications

• Familiarity with cloud platforms (AWS, Microsoft Azure) for infrastructure deployment and management
• Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack)
• Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams
• Experience with infrastructure as code (IaC) tools (e.g., Terraform, Ansible)
• Understanding of machine learning concepts and their implications for infrastructure; continuous learning mindset to stay abreast of cutting-edge DevOps and AI advancements

TS/SCI With Polygraph Is Required.