Senior Infrastructure Engineer - AI/ML

4+ years of hands-on infrastructure/platform/DevOps experience with production systems. Strong understanding of infrastructure engineering principles: scalability, reliability, observability, and automation. Solid experience with Kubernetes in production environments, including troubleshooting and optimization. Proficiency with Infrastructure-as-Code tooling (Terraform, Helm, or similar). Experience with at least one major cloud platform (AWS, Azure, GCP), including networking, security, and compute services. Strong programming skills, particularly in Python and/or Go. Experience contributing to technical initiatives or mentoring junior team members. Understanding of CI/CD practices, GitOps workflows, and infrastructure automation principles. Comfortable working independently and in distributed teams. Ability to provide and constructively receive feedback. Available for collaboration during overlap with US Central Time zone.

Contribute to Nebari and design reusable, modular infrastructure components for sovereign AI deployments. Develop composable MLOps components and infrastructure patterns for model training, serving, monitoring, and CI/CD. Design and implement observability, monitoring, and cost optimization strategies for AI/ML workloads. Collaborate with ML engineers to optimize infrastructure for various AI applications. Contribute to open-source MLOps tooling and Kubernetes ecosystem projects. Work with clients to deploy, configure, and optimize their sovereign AI infrastructure. Collaborate with a fully remote distributed team using asynchronous communication methods.