* Salário: R$ 3.000 a R$ 6.000 por mês (estimado)
* O valor exibido é uma estimativa calculada com base em dados públicos e referências do mercado. Não garantimos que este seja o salário oferecido para esta vaga específica.
Área: Tecnologia da Informação
Nível: Junior
We are building scalable Kubernetes and Linux infrastructure designed for GPU workloads, efficient scheduling, and repeatable automation at scale. As a Middle DevOps Engineer, you will support and enhance Kubernetes environments with Volcano, operate Linux compute nodes, and deliver automation in Python and Bash within a client-facing team. Apply to help researchers run AI jobs smoothly on reliable compute platforms.
Responsibilities
- Install, configure, and operate GPU-enabled Kubernetes clusters and standalone Linux compute environments to maintain optimized scheduling and performance
- Configure and administer Volcano job scheduling, including queue setup, POD execution, GPU allocation, and namespace quota enforcement
- Manage Kubernetes end to end, covering namespaces, RBAC, resource quotas, and workload isolation approaches
- Build and maintain Python and Shell automation to streamline job submission, resource provisioning, and system reporting
- Partner with orchestration, optimization, and observability teams to improve scheduling efficiency, increase capacity utilization, and simplify researcher workflows
- Track infrastructure health and resource utilization, providing data and feedback for optimization and reporting needs
- Drive enhancements to infrastructure, tooling, and automation workflows to improve performance, scalability, and usability
- Support operational processes that ensure a smooth and efficient experience for researchers running diverse AI and computational workloads
Requirements
- Hands-on background with 2+ years of experience in DevOps or infrastructure engineering within complex, large-scale environments
- Strong expertise in Kubernetes administration and orchestration, including namespaces, POD scheduling/distribution, PVC, NFS, and resource quota management
- Practical experience with the Volcano scheduler for GPU job execution, queue configuration, and workload prioritization integrated with Kubernetes
- Proven ability to operate GPU cluster environments in Kubernetes as well as on standalone Linux compute nodes
- Advanced Python scripting skills for infrastructure automation, plus proficiency in UNIX Shell scripting such as Bash
- Strong Linux system administration skills, including troubleshooting, performance tuning, and configuration management
- Solid understanding of infrastructure automation and orchestration concepts and related tooling
- Fluent English communication skills (spoken and written) for direct client interaction
Nice to have
- Knowledge of Helm package management for Kubernetes applications
- Familiarity with monitoring and observability solutions, particularly Prometheus, Grafana, and Loki
- Skills in Infrastructure as Code tools such as Terraform
- Background in multi-cloud Kubernetes environments including Amazon EKS and Google GKE
- Understanding of Azure Networking including VPN, ExpressRoute, and network security
- Familiarity with AI-assisted coding tools such as GitHub Copilot, ChatGPT, and Claude
- Experience with hybrid (cloud and on-premises) scheduling and resource optimization