Senior DevOps Engineer

About the role

Founded in 2007 and headquartered in Columbia, Maryland, Synergy ECP is a leading provider of cybersecurity, software and systems engineering and IT services to the U.S. intelligence and defense communities. The company leverages its expertise in data transport solutions, software and systems engineering, and other solutions to deliver critical and innovative capabilities to high-level decision makers that enhance our nation’s security.

In an ultra-competitive environment, Synergy ECP has thrived by adhering to our name, making sure excellence is displayed by our Employees, to our Customers and by Improving Performance (ECP). It’s what sets us apart, enabling us to be an autonomous yet agile business that delivers huge results—showing we’re ready to meet our customers’ evolving demands. Synergy ECP has earned a client list that includes numerous Fortune 100 companies, in addition to multiple branches of the US government and military services.

Position Overview

We are seeking a highly experienced and technically proficient Senior DevOps Engineer to play an integral role in our team, focusing on deploying infrastructure and engineering workflows and processes to support enterprise AI rollouts. This position requires deep expertise in DevOps principles, including containerization, CI/CD pipeline architecture, and AI model lifecycle management. The ideal candidate will be adept at ensuring robust, scalable, and efficient deployment and maintenance of AI applications at an enterprise scale.

What You'll Be Doing

● Design, implement, and maintain robust infrastructure for enterprise AI applications in cloud environments (AWS, Microsoft Azure)

● Develop and optimize engineering workflows and processes to support AI model development, deployment, and maintenance.

● Architect and manage CI/CD pipelines for continuous integration and continuous delivery of AI models and applications.

● Implement and manage containerization solutions using technologies like Docker and Kubernetes.

● Ensure efficient AI model 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.

● Continuously research and implement new DevOps tools and practices to enhance efficiency.

Required Experience

● B.S. in a relevant technical field with 12 years of experience, or M.S. in a relevant technical field with 10 years of experience.

● 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.

● Familiarity with cloud platforms (AWS, Microsoft Azure) for infrastructure deployment and management.