Engineering Manager (Developer Tooling)

Join our team as an Engineering Manager (Developer Tooling) and lead the design, building, and operation of our CI/CD pipelines. You will set the technical direction for our pipeline platform, integrate AI capabilities into the developer workflow, and drive measurable improvements in pipeline reliability and developer wait times. This is a critical role with significant impact on engineering velocity and reliability across the company.

• Lead and manage a team responsible for designing, building, and operating CI/CD pipelines, ensuring the reliability and efficiency of the pipeline platform.
• Set the technical direction for the pipeline platform, partnering with Infrastructure Services and product engineering teams to deliver a fast, reliable, and self-service path to production.
• Integrate AI capabilities into the developer workflow, including AI code review, AI generated tests, and intelligent test selection, to enhance the development process.
• We’re looking for people who are relentlessly curious and committed to continuous learning
• Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes
• 7 or more years of engineering experience with 2 or more years managing engineers, ideally in DevOps, platform engineering, or developer experience teams
• Strong hands-on background with CI/CD systems including Jenkins, GitHub Actions, GitLab CI, Tekton, or similar, including pipeline as code patterns
• Experience designing shared libraries, templates, or platforms used by many internal teams
• Demonstrated ability to balance hands-on technical leadership with people management responsibilities
• A service mindset measured by the productivity and happiness of the engineers you serve
• Working knowledge of ArgoCD or comparable GitOps tooling and artifact management systems like Artifactory, Nexus, or Harbor
• Hands-on experience integrating AI tooling into the development workflow including AI code review, AI test generation, AI coding assistants, or engineering intelligence platforms such as LinearB, DX, Jellyfish, Faros, or similar
• Strong written and verbal communication with the ability to translate technical strategy for both engineers and non-technical stakeholders
• Solid understanding of Kubernetes, containers, and cloud native deployment models