DevOps Software Engineer

Leidos•Bethesda, MD
•$107,900 - $195,050•Hybrid

About The Position

Leidos is hiring a TS/SCI-cleared DevOps Software Engineer to work with a dynamic team designing, developing, and deploying a technology stack for the DOMEX Data Discovery Platform (D3P) Modernization program. The program supports the client’s mission to centralize and standardize the tasking, collection, processing, exploitation, and dissemination of Open Source Intelligence across the Defense Intelligence Enterprise. The role contributes to the design, deployment, and maintenance of a full-stack containerized microservices architecture, along with technical systems administration, installation, and configuration. It involves fostering a DevOps culture and collaborating with systems engineering, architecture, development, security, operations, and integration teams. Most work is conducted on-site at the client location in Bethesda, Maryland, with a flexible schedule and occasional remote work. The engineer will work with developers, software integrators, and system administrators to maintain production data pipelines and scalable infrastructure, improve CI/CD processes, configure Kubernetes continuous deployments, and support hybrid and secure multi-tenant GPU environments. The work also includes systems engineering documentation, Agile planning and coordination, and troubleshooting in a dynamic environment.

Requirements

  • Bachelor’s degree in Engineering, Computer Science, Systems Engineering, or a related field, or equivalent experience, with 8 or more years in software development, systems engineering, or a related field; 6 or more years of experience with a master’s degree.
  • Active Top Secret/SCI security clearance and ability to obtain and maintain a TS/SCI with Polygraph clearance.
  • Knowledge of Linux operating systems and Kubernetes environments.
  • At least one DoD 8570.01-M IAT Level II or higher certification, such as CCNA Security, CySA+, Security+ CE, SSCP, or CISSP (or Associate).
  • GitLab CI/CD pipeline development experience.
  • Ability to obtain Privileged User Account (PUA) certification per DoD 8570 policy.
  • Container and container-orchestration experience, specifically with Kubernetes, including troubleshooting Ingress/Gateway API, multi-tenant GPU sharing, Helm chart design and build, pod disruption budgets, and affinity/anti-affinity rules.
  • Familiarity with external-secrets, ArgoCD, cert-manager, and ECK (Elasticsearch).
  • Comfort with Elasticsearch, Logstash, and Kibana.
  • Demonstrated ability to participate in cross-functional planning, coordination, and task execution.

Nice To Haves

  • Experience with systems at scale.
  • Experience or knowledge of key Agile processes and techniques.
  • Development experience with languages or tools such as Bash, PowerShell, SALT, Python, Groovy, or Java.
  • Experience on a production or enterprise system.
  • Experience with Kafka or other message-passing systems such as AMQP or JMS.
  • Experience with Kubernetes monitoring tools such as Prometheus, Grafana, or OpenTelemetry.
  • Experience with SALT for deployment automation.
  • Experience with Nexus.

Responsibilities

  • Deploy, triage, and maintain a production big data pipeline using a microservices architecture running on Kubernetes, an Elasticsearch backend, and Kafka messaging.
  • Enhance and maintain CI/CD and DevOps scripts and processes, including AI-integrated solutions for failure analysis, security, and compliance.
  • Design, develop, and support scalable, redundant infrastructure in physical and virtualized environments.
  • Configure Kubernetes continuous deployments using tools such as Helm, YAML, and ArgoCD.
  • Collaborate with system engineers to design solutions for new features and requirements.
  • Provide technical input to systems engineering documentation and diagrams or models in coordination with systems engineering and architecture team members.
  • Participate in Agile release planning, scrum of scrums, bug triage, design sessions, and other meetings.
  • Develop PaaS solutions for hybrid deployments and secure multi-tenant GPU sharing in Kubernetes environments.
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