Poly

Parsons Corporation•Columbia, MD

5d•$148,300 - $266,900

About The Position

Parsons is hiring an experienced DevOps/platform engineer who thrives in a fast-paced environment. This role involves owning infrastructure end to end and shaping how AI is deployed and delivered across a national mission, supporting the United States Cyber Command (USCC). The team is establishing USCYBERCOM’s AI Enterprise capability, a central hub for moving AI solutions from prototype to secure, governed, enterprise-scale services. The Senior Platform / DevOps Engineer will build and operate the infrastructure, pipelines, and control-plane guardrails necessary for the command to adopt AI safely and at scale, with significant mission impact.

Requirements

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

Nice To Haves

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

Responsibilities

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.