Site Reliability Engineer - Foundation Team

Global-e (Nasdaq: GLBE) is the world’s leading platform for global direct-to-consumer e-commerce, enabling brands and retailers to seamlessly sell worldwide, delivering localized experiences across markets.

Trusted by some of the world’s most recognized brands including Adidas, Alo Yoga, Logitech, Hugo Boss, Marc Jacobs, and Victoria’s Secret, we operate on a massive global scale through dynamic teams across North America, EMEA, and APAC.

Our technology-based end-to-end solution combines advanced localisation capabilities, streamlined global operations and extensive big-data analytics, covering everything merchants need to scale worldwide. We’re a fast-moving, highly collaborative company where innovation, creativity, ownership, and impact are part of everyday work.

As a DevOps/SRE Engineer on our Foundation team, you will help build, operate, and continuously improve the platform infrastructure that underpins all of Global-e's microservices. You'll work at the intersection of infrastructure engineering and reliability — automating deployments, hardening systems, and ensuring our platform scales reliably to handle millions of transactions worldwide.

This is a mid-level role for someone who is hands-on with cloud infrastructure and eager to grow their skills across a modern, high-traffic production environment. You'll collaborate closely with software engineers, platform architects, and product teams to keep our systems fast, resilient, and operationally excellent.

This role reports to the Engineering Manager for the Foundation team and is based out of our Dublin, Ireland office.

You Will:

• Own Infrastructure as Code: Write, maintain, and improve Terraform modules to provision and manage cloud resources on AWS (EKS, RDS, Kinesis, and more).
• Support and Improve CI/CD Pipelines: Build and maintain reliable deployment pipelines that enable engineering teams to ship with speed and confidence.
• Ensure Platform Reliability: Define and track SLOs/SLAs, respond to incidents, conduct post-mortems, and drive systemic improvements to reduce toil and prevent recurrence.
• Monitor and Observe: Implement and maintain observability tooling — metrics, logging, alerting, and dashboards — to provide clear visibility into system health.
• Scale Kubernetes Workloads: Help manage and evolve our EKS clusters, ensuring workloads are performant, cost-efficient, and fault-tolerant.
• Embrace AI-Augmented Operations: Leverage and help expand our growing use of AI tooling — from AIOps and anomaly detection to AI-assisted incident response and infrastructure optimisation — as we invest heavily in bringing AI into our day-to-day engineering workflows.