DevOps Engineer, Infrastructure & Security

Responsibilities

• Design, develop, and maintain robust CI/CD pipelines to automate the deployment of lowside and highside products.
• Collaborate closely with product and engineering teams to enhance existing application code for improved compatibility and streamlined integration within automated pipelines.
• Contribute to the overall architecture and design of deployment systems, bringing new ideas for increased efficiency and reliability.
• Troubleshoot and resolve complex deployment issues, ensuring minimal disruption to development cycles.
• Develop a deep understanding of product and ML architectures to facilitate seamless integration and deployment.
• Document pipeline processes and configurations to ensure maintainability and knowledge transfer.
• Proactively incorporate security best practices into all stages of the CI/CD pipeline.
• Drive standardization and foster collaboration across different product teams to achieve a unified and efficient SDLC.

Requirements

• Active TS/SCI clearance and willingness to upgrade to CI Poly.
• 2-3 years of experience as a DevOps Engineer, DevSecOps Engineer, Software Engineer with strong CI/CD focus, or similar role.
• Proven track record of building or significantly enhancing CI/CD pipelines.
• Experience configuring and adapting application code to integrate with CI/CD environments.
• Experience with containerization and deployment technologies like Kubernetes, Terraform, Docker.
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Strong proficiency in scripting and automation (Python, Bash, PowerShell).
• Familiarity with CI/CD platforms (Jenkins, GitLab CI, GitHub Actions, Azure DevOps).
• Knowledge of software architecture, system design, and version control systems.
• Comfort in rapidly changing, fast-paced environments with passion for automated solutions.
• Basic understanding of security best practices and eagerness to integrate them.
• Hunger for learning new technologies, especially integrating ML into automated workflows.
• Strong problem-solving, analytical, collaboration, and communication skills.

Nice-to-Haves

• Experience with containerization technologies (Docker, Kubernetes).
• Exposure to machine learning lifecycles or MLOps concepts.
• Prior experience in classified environments.