Poly

Parsons Corporation•Columbia, MD

4d•$148,300 - $266,900

About The Position

Parsons is hiring a Senior Platform DevOps Engineer to support the United States Cyber Command (USCC) by helping establish its AI Enterprise capability. This capability serves as a central hub for moving AI solutions from prototype to secure, governed, enterprise-scale services. The engineer will build and operate infrastructure, pipelines, and control-plane guardrails that enable safe, scalable AI adoption across the mission. The role provides embedded operations support, capability integration, and rapid prototyping for AI-enabled tools. It covers infrastructure and engineering workflows across cloud environments, including AWS and Microsoft Azure, as well as on-premises, air-gapped, and classified environments. The engineer will work with AI/ML engineers and data scientists to deploy and maintain models, agents, and applications, while supporting system performance, security, scalability, and security accreditation (RMF/ATO). An active TS/SCI clearance with polygraph is required.

Requirements

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

Nice To Haves

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

Responsibilities

Provide embedded operations support, capability integration, and rapid prototyping for AI-enabled tools in support of the customer.
Design, implement, and maintain infrastructure for enterprise AI applications in cloud, on-premises, air-gapped, and classified environments.
Develop and optimize workflows and processes for AI model and agent development, deployment, and maintenance.
Architect and manage CI/CD pipelines for AI models, agents, and applications.
Implement and manage containerization and orchestration solutions using Docker and Kubernetes.
Build and maintain control-plane guardrails for identity, policy enforcement, approvals, audit and logging, and observability.
Manage AI model and agent lifecycles, including versioning, monitoring, and scaling.
Collaborate with AI/ML engineers and data scientists to streamline deployments and optimize resource utilization.
Oversee the performance, security, and scalability of AI infrastructure and support RMF/ATO security accreditation of AI systems.
Research and implement DevOps tools and practices to enhance efficiency.