We are looking for a seasoned Senior DevOps Engineer with extensive experience in containerization, deploying and configuring applications, CI/CD pipelines, and a combination of cloud and on-premises deployments. The ideal candidate will also have strong skills in configuring ports, firewalls, and managing network traffic. Exposure to software engineering and/or data engineering is a big plus. Design, implement, and manage CI/CD pipelines for efficient application deployment and operations. Utilize containerization technologies (such as Docker, Kubernetes) to deploy applications in cloud environments and on-premises. Deploy and configure applications on AWS and other cloud platforms. Manage and configure network infrastructure, including ports, firewalls, and network traffic monitoring. Work within classified spaces maintaining the highest levels of security and compliance. Troubleshoot and resolve technical issues across development, deployment, and operational environments. Collaborate with cross-functional teams to deliver robust and scalable solutions. Stay informed of the latest developments in DevOps practices and integrate best practices. Potentially take on software engineering and/or data engineering tasks as needed. Sr Principal DevOps Engineer: 08 Years with Bachelor's in related field of study, 06 Years with Masters, 04 Years with PhD or 04 additional years in lieu of a degree. US Citizenship with Active DoD Top Secret clearance with a reinvestigation date occurring in the last 6 years. Ability to obtain Special Program Access (SAP) Proven experience with AWS and other cloud platforms. Extensive knowledge of containerization and deployment technologies (Docker, Kubernetes). Proficiency with CI/CD pipelines and automation tools. Strong understanding of network configuration, including ports, firewalls, and network traffic management. Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Experience working in classified spaces and adhering to security protocols. Exposure to software engineering and/or data engineering. Exposure to generative AI technologies and their applications. Familiarity with graph data structures and databases. Knowledge of programming and scripting languages for automation.