Role overview

Scale is building reliable AI systems for critical decisions and is seeking a DevOps Engineer to strengthen infrastructure and security for its public sector operations. You will establish and enhance CI/CD pipelines that automate deployment across the company’s product suite, moving the organization from manual processes to a unified, automated system that integrates machine learning workflows seamlessly into the software development lifecycle.

Key responsibilities

Design, develop, and maintain robust CI/CD pipelines that automate the deployment of lowside and highside products.
Collaborate with product and engineering teams to enhance application code for improved compatibility and integration within automated pipelines.
Contribute to the overall architecture and design of deployment systems while bringing new ideas to improve efficiency and reliability.
Troubleshoot and resolve complex deployment issues to minimize disruption to development cycles.
Build a comprehensive understanding of product and machine learning architectures to facilitate seamless integration and deployment.
Document pipeline processes and configurations to ensure maintainability and enable effective knowledge transfer across teams.
Proactively integrate security best practices throughout all stages of the CI/CD pipeline and drive standardization across product teams.

Requirements

An active TS/SCI security clearance and willingness to pursue CI Poly certification; this is mandatory and candidates without at least TS/SCI clearance will not be considered.
A minimum of two to three years of experience as a DevOps Engineer, DevSecOps Engineer, Software Engineer with strong CI/CD focus, or equivalent role.
Proven experience building or significantly enhancing CI/CD pipelines and configuring application code for integration with evolving CI/CD environments.
Working proficiency with containerization and deployment technologies such as Kubernetes, Terraform, and Docker.
Strong scripting and automation skills in languages including Python, Bash, or PowerShell, along with familiarity with CI/CD platforms like Jenkins, GitLab CI, GitHub Actions, or Azure DevOps.
Knowledge of software architecture, system design, and version control systems, plus comfort working in rapidly changing, fast-paced environments.
Strong problem-solving, analytical, collaboration, and communication skills, with a commitment to learning new technologies and integrating machine learning into automated workflows.

What makes this role worth considering

This position offers the opportunity to work at the intersection of DevOps and emerging AI/ML technologies, directly shaping how machine learning components are integrated into deployment workflows. You’ll be collaborating across multiple product teams to establish unified development practices while working on systems that support government agencies and industry leaders in deploying AI applications with real-world impact.