Principal DevOps Engineer

Leidos•Fort Meade, MD

1d•$154,050 - $278,475

About The Position

Leidos has a new and exciting opportunity for a Principal DevOps Engineer in our Intelligence Sector's Cyber & Analytics Business Area (CABA). Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in National Security! Job Summary The Principal DevOps Software Engineer will support the design, deployment, and maintenance of software systems across containerized and high‑performance computing environments. This role includes DevOps pipeline development, Kubernetes administration, GPU configuration, automated testing, and software debugging. Strong collaboration and clear documentation are essential to ensure reliable delivery and ongoing system support.

Requirements

Bachelor’s degree in Computer Science or related discipline and Twenty (20) or more years of software engineering experience.
Four (4) years of additional SWE experience on projects with similar software processes may be substituted for a bachelor’s degree.
Experience with GPU/CUDA development for performance‑critical applications.
Familiarity with message queue implementation and communication protocols.
Knowledge of Linux system programming and development environments.
Understanding of RF signals analysis or satellite communications system design and theory.
Strong analytical and problem‑solving abilities.
Clearance Requirement: Active TS/SCI with polygraph

Responsibilities

Design, implement, and maintain DevOps pipelines for C++ or Python applications, including Kubernetes/K8s deployment, Helm chart creation, and pod definition.
Administer and configure Kubernetes clusters to support availability, scalability, and security requirements.
Identify, debug, and correct defects in existing software using effective troubleshooting techniques.
Configure and optimize GPU resources for performance‑critical applications using CUDA or related technologies.
Implement automated testing and deployment scripts using tools such as Jenkins or GitLab CI/CD.
Collaborate with system architects and project managers to ensure software meets user requirements and delivery schedules.
Maintain comprehensive documentation for software designs, processes, and interfaces.