About the Role
We’re looking for an experienced Site Reliability Engineer (SRE) to help us scale our platform with reliability, observability, and operational excellence at the core. You’ll partner with engineers and data scientists to build, automate, and maintain the infrastructure that powers our core platform—including data pipelines, ML workloads, and real-time analytics systems.
This is a (very) hands-on, high-impact role with visibility across the stack and the opportunity to shape the future of our infrastructure and operations. We're hiring onsite at our Supercomputing Research Facility in Dunwoody, GA.
Key Responsibilities
- Design, build, and maintain scalable infrastructure to support real-time analytics and machine learning workloads
- Improve system reliability and performance through automation, observability, and proactive capacity planning
- Respond to customer support issues as well as site operations issues in a timely manner. This position requires participation in a call-in rotation
- Own and evolve CI/CD pipelines, deployment automation, rollback mechanisms, and config management
- Own processes around Supercomputing facility physical support, including device management, inventory, basic network and system administration, NVidia DGX cluster administration and advanced datacenter systems
- Implement and maintain monitoring, alerting, and incident response processes (SLOs, runbooks, on-call rotations)
- Collaborate across engineering teams to drive a culture of performance and reliability
- Ensure security, compliance, and operational readiness across our infrastructure
- Drive post-incident analysis and continuous improvement initiatives
What Will Help You Succeed
- 8+ years of experience in SRE, DevOps, or infrastructure engineering roles
- 5+ years of experience with datacenter operations and/or system and network administration
- Experience with containerization (Docker), and orchestration (Kubernetes)
- Strong knowledge of Linux systems, networking, and systems performance tuning, including strong-to-expert facility with SSH, terminal, shell and the Linux command line.
- Solid understanding of infrastructure-as-code (e.g., Terraform, Ansible)
