Staff DevOps Engineer - Kubernetes Platform Lead (Remote)

Nextiva; Región Centro; Híbrido; MXN 900.000 - 1.400.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Career development

Flexible work arrangements

Descripción de la vacante

Nextiva is seeking a Staff DevOps Engineer to lead the design and evolution of our multi-cluster Kubernetes platform. You will own architecture standards, drive platform reliability, and enable engineering teams with self-service access to compute, environments, and observability.

You’ll collaborate with AI/ML teams on training and inference workloads, manage cost optimization, and mentor senior engineers while shaping the direction of platform tooling and governance across the organization.

Formación

• Bachelor’s degree or equivalent experience in computer science or related field.

Responsabilidades

• Own the architecture and roadmap for multi-cluster Kubernetes platform, including scaling, upgrades, and multi-tenancy.
• Establish GitOps-based deployment workflows using Argo CD or Flux.
• Design and evolve a developer platform providing self-service access to compute, environments, and observability.
• Define platform standards for GPU/ML workload scheduling on Kubernetes.
• Partner with AI/ML teams on infrastructure requirements for training/inference workloads.
• Drive capacity planning and cost optimization across Kubernetes and cloud infra.
• Define and own platform reliability with SLOs, incident leadership, and postmortems.
• Mentor engineers and influence cross-team platform decisions.

Conocimientos

Kubernetes

GitOps

Terraform

Pulumi

Argo CD

Istio

Linux

Cloud (AWS, GCP)

Observability

Cost optimization

Educación

Bachelor's degree in Computer Science or related field

Herramientas

Argo CD

Flux

Terraform

Pulumi

Prometheus

Grafana

Descripción del empleo

Nextiva is seeking a Staff DevOps Engineer to lead the design and evolution of our multi-cluster Kubernetes platform. You will own architecture standards, drive platform reliability, and enable engineering teams with self-service access to compute, environments, and observability.

You’ll collaborate with AI/ML teams on training and inference workloads, manage cost optimization, and mentor senior engineers while shaping the direction of platform tooling and governance across the organization.