Site Reliability Engineer with Fleet Engineering

Develop and maintain automation solutions that improve the reliability, scalability, and operational efficiency of infrastructure spanning more than 2,000 machines across global cloud environments. Design and enhance deployment pipelines, testing frameworks, and operational tooling to support the continued growth of a platform serving millions of managed devices worldwide. Troubleshoot complex infrastructure and distributed systems issues to ensure high availability while helping teams identify and address performance and scalability challenges. Contribute to critical projects such as cluster build out by building automation that enables the rapid and repeatable deployment of new sovereign, regional, and purpose-built cloud environments. Partner with other engineering teams, product management, and business partners across multiple teams and time zones to understand platform dependencies, seek opportunities for improvement, and deliver solutions that enhance reliability and reduce operational overhead.

Reliability Engineering, Vehicle Fleets, Reliability Engineering, Vehicle Fleets, DevOps, Production Systems, Cloud Computing, Automation, Ansible, RSpec, 4+ years of experience in Site Reliability Engineering, DevOps, Infrastructure Engineering, or a related role supporting cloud-based production environments. Experience developing and maintaining infrastructure automation using Ansible. Experience programming in Ruby and developing automated tests using RSpec or comparable testing frameworks. Experience administering and troubleshooting Linux-based systems and distributed infrastructure environments. Experience designing, implementing, and maintaining CI/CD pipelines, including GitLab CI. Experience supporting large-scale infrastructure environments consisting of hundreds or thousands of systems. Preferred Qualifications: Familiarity with AWS or other public cloud platforms and hybrid infrastructure environments. Knowledge of monitoring, observability, and reliability engineering practices and tooling. Familiarity with Kubernetes concepts and containerized application platforms. Experience leveraging AI-assisted development tools to improve software development, automation, operational analysis, and engineering productivity