DevOps Engineer: CI/CD, Security & ML Integration

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

Job summary

United States Digital Space LLC is seeking a DevOps Engineer for the Public Sector, focused on building automated CI/CD pipelines and integrating ML components into the SDLC. You will collaborate with product and engineering teams to enhance deployment processes, improve reliability, and embed security into every stage of development.

Candidates should have strong scripting and cloud experience, plus a willingness to learn ML lifecycle concepts.

Qualifications

• Active TS/SCI clearance with willingness to upgrade to CI Poly.
• Experience designing, developing, and maintaining robust CI/CD pipelines.
• Ability to collaborate with product and engineering teams to improve automation.
• Knowledge of secure SDLC practices and deployment security.

Responsibilities

• Design, develop, and maintain CI/CD pipelines for lowside/highside products.
• Collaborate with product and engineering teams to improve code for automation.
• Contribute to deployment system architecture for efficiency and reliability.
• Troubleshoot complex deployment issues with minimal disruption.
• Understand product and ML architectures to enable integrated workflows.
• Document pipelines and configurations for maintainability.
• Implement security best practices at all SDLC stages.
• Promote standardization across product teams for unified SDLC.

Skills

CI/CD pipelines

Kubernetes

Terraform

Docker

Python scripting

Security best practices

Cloud platforms

Automation

Collaboration

SDLC

Tools

Jenkins

GitHub Actions

Azure DevOps

Job description

United States Digital Space LLC is seeking a DevOps Engineer for the Public Sector, focused on building automated CI/CD pipelines and integrating ML components into the SDLC. You will collaborate with product and engineering teams to enhance deployment processes, improve reliability, and embed security into every stage of development.

Candidates should have strong scripting and cloud experience, plus a willingness to learn ML lifecycle concepts.