DevSecOps Engineer — CI/CD & ML-Enabled SDLC (TS/SCI)

United States Digital Space LLC; Washington (District of Columbia); On-site; USD 178,000 - 279,000; Full time

Benefits offered by this job

Equity compensation

Health benefits

Paid time off

Learning stipend

Job summary

United States Digital Space LLC in Washington, DC is seeking DevOps Engineers, Public Sector, to design and implement robust CI/CD pipelines, advancing SDLC automation and streamlining deployments across products. You will collaborate with product and engineering teams to enhance applications for automated pipelines, integrate ML tasks into workflows, and embed security best practices.

A strong candidate has 2–3 years of DevOps/DevSecOps experience, cloud familiarity, and a willingness to learn

Qualifications

• Active TS/SCI clearance and eligibility for CI Poly.
• 2–3 years in DevOps/DevSecOps or CI/CD focused roles.
• Experience building and maintaining CI/CD pipelines.
• Proficient with Kubernetes, Docker, Terraform.
• Scripting and automation skills (Python, Bash, PowerShell).
• Experience with AWS, Azure, or GCP.

Responsibilities

• Design, develop, and maintain robust CI/CD pipelines for lowside and highside products.
• Collaborate with product and engineering teams to improve integration with pipelines.
• Contribute to deployment architecture and system design for reliability.
• Troubleshoot deployment issues to minimize development downtime.
• Document pipelines and security practices across the SDLC.
• Drive standardization and cross-team collaboration for an efficient SDLC.

Skills

CI/CD

Scripting

Cloud platforms

Problem solving

Communication

Tools

Kubernetes

Docker

Terraform

Jenkins

GitHub Actions

GitLab CI

Azure DevOps

AWS

Job description

United States Digital Space LLC in Washington, DC is seeking DevOps Engineers, Public Sector, to design and implement robust CI/CD pipelines, advancing SDLC automation and streamlining deployments across products. You will collaborate with product and engineering teams to enhance applications for automated pipelines, integrate ML tasks into workflows, and embed security best practices.

A strong candidate has 2–3 years of DevOps/DevSecOps experience, cloud familiarity, and a willingness to learn