Role Overview
Join a global team of 550+ professionals building infrastructure and software that supports the entire digital ecosystem. As a DevOps Engineer, you will be responsible for designing, deploying, and maintaining infrastructure and services that enable scalable and secure AI inference workloads on-premises.
What You Will Do
Design, develop, and maintain infrastructure for AI inference workloads, including GPU scheduling, model deployment pipelines, and data access patterns in on-prem environments. Build and manage monitoring and observability tools for AI inference platforms, including dashboards, alerts, and runbooks for model health and system performance.
Why It Might Be a Fit
Strong understanding of Kubernetes architecture, including CNI, CSI, operators, ingress/gateway, and control plane components. Hands-on experience operating and troubleshooting production Kubernetes clusters. Strong Linux and networking troubleshooting skills, including DNS, routing, firewalling, TLS, MTU, connectivity and performance issues.
Requirements
- Strong understanding of Kubernetes architecture
- Hands-on experience operating and troubleshooting production Kubernetes clusters
- Strong Linux and networking troubleshooting skills
- Ability to develop automation and operational tooling using Python, Go, or Bash
- Experience with Terraform, Ansible, or similar IaC/configuration management tools
- Experience with VictoriaMetrics/Grafana or similar monitoring, alerting, and troubleshooting tools
- Strong experience with Git-based workflows and CI/CD pipelines
Benefits
- Competitive compensation
- Flexible working hours and hybrid or remote options
- Work from anywhere in the world for up to 45 days per year
- Private medical insurance for you and your family
- Extra paid vacation and sick leave days
- Support for life’s important moments and celebrations
- Language courses to help you connect and grow
- Modern, welcoming offices with snacks, drinks, and entertainment
- Team sports and social activities
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