Staff DevOps Engineer

Redefine the future of customer experiences. One conversation at a time.

At Nextiva, we’re reimagining how businesses connect, bringing together customer experience and team collaboration on a single, conversation centric platform. Powered by AI, driven by human innovation.

Our culture is forward thinking, customer obsessed and built on the belief that meaningful connections drive better business outcomes. Whether it’s through our signature Amazing Service®, the technology we create, or the experiences we cultivate, connection is at the core of who we are.

If you’re ready to collaborate with incredible people, make an impact, and help businesses everywhere deliver truly amazing experiences, this is where you belong.

While this role is open to remote candidates across Mexico, team members located within 80 kilometers of our Guadalajara office (Calle Amado Nervo 2200, Jardínes del Sol, 45050 Zapopan, Jal.) are expected to work onsite to support collaboration, speed, and execution.

Nextiva is looking for a Staff DevOps Engineer to lead the design and evolution of our platform engineering practice, with deep technical ownership of Kubernetes infrastructure.

This is an individual-contributor technical leadership role. You’ll help define how engineering teams build, deploy, and operate software by establishing platform architecture, standards, and paved roads that make infrastructure easier to consume without sacrificing reliability, security, or scalability.

Nextiva operates a globally available, redundant microservices architecture and positions reliability, API accessibility, and adaptability as key elements of its technology platform. This role will help evolve the infrastructure behind that environment while supporting the growing needs of engineering and AI/ML workloads.

What you’ll do

• Own the architecture and roadmap for our multi-cluster Kubernetes platform, including scaling, upgrades, and multi-tenancy.

• Establish GitOps-based deployment workflows using technologies such as Argo CD or Flux.

• Design and evolve an internal developer platform that provides engineering teams with self-service access to compute, environments, and observability.

• Architect service mesh, networking, and ingress strategies for reliable and secure communication across services.

• Define platform standards for GPU and ML workload scheduling and resource management on Kubernetes.

• Partner with AI/ML teams on infrastructure requirements for training and inference workloads.

• Drive capacity planning and cost optimization across Kubernetes and cloud infrastructure.

• Set technical direction and review architecture for platform-impacting changes across engineering.

• Define and own platform reliability through SLOs, incident-response leadership, and postmortems.

• Mentor experienced engineers and represent platform engineering in cross-organizational technical decisions.

• Influence teams toward common platform standards without relying on direct reporting authority.

What you bring

• Bachelor’s degree in Computer Science or a related field, or equivalent work experience.

• 8+ years of DevOps, platform, or infrastructure engineering experience.

• 5+ years of hands-on Kubernetes experience in production, including cluster architecture, upgrades, and multi-tenant environments.

• Strong hands-on experience operating cloud infrastructure across AWS and Google Cloud Platform (GCP).

• Strong GitOps experience with Argo CD or Flux.

• Strong Infrastructure-as-Code experience with Terraform or Pulumi.

• Deep understanding of container orchestration, networking, ingress, and service mesh technologies such as Istio, Linkerd, or Cilium.

• Experience with middleware and messaging technologies such as Nginx, Kafka, and Redis at scale.

• Experience with GPU scheduling, node pools, and resource quotas supporting ML/AI training or inference workloads in GKE and EKS.

• Experience designing internal developer platforms or paved-road tooling for engineering organizations.

• Strong Linux, networking, storage, and security fundamentals.

• Experience operating observability platforms such as Prometheus, Grafana, Datadog, or OpenTelemetry at platform scale.

• Excellent communication skills with the ability to influence technical direction across teams.

• Demonstrated ability to understand, calculate, forecast, and optimize cloud and Kubernetes infrastructure costs, including evaluating the cost implications of architecture, capacity, compute, and resource-allocation decisions.

• Experience with capacity planning and resource optimization, balancing performance, reliability, scalability, and infrastructure cost.

Additional experience that will help you succeed

• Kubernetes policy-as-code and security tooling such as OPA/Gatekeeper, Kyverno, or image-scanning technologies.

• AWS, GCP, Azure, CKA, or CKS certifications.

AI literacy

AI matters to this role primarily as an infrastructure and platform workload, not simply as an end-user productivity tool.

• Experience designing infrastructure capable of supporting ML/AI training or inference workloads.

• Understanding of GPU scheduling, resource allocation, node pools, quotas, reliability, and cost considerations for AI workloads.

• Ability to work with AI/ML engineering teams to translate workload requirements into scalable Kubernetes and cloud platform capabilities.

Nextiva DNA (Core Competencies)

Nextiva’s most successful team members share common traits and behaviors:

• Drives Results: Action-oriented problem solvers who quickly bring clarity and simplicity to ambiguity, challenge the status quo, and lead meaningful change; celebrating wins to fuel momentum. They act swiftly and pragmatically, learning and improving as they go.

• Critical Thinker: Data-driven, forward-thinking individuals who identify key drivers, anticipate risks, and deliver clear recommendations. They confidently leverage AI and automation to reduce friction, improve decision-making, and focus on higher-value work.