Senior Kubernetes Platform Engineer — Multi-Region Scale

TensorWave; Las Vegas (NV); On-site; USD 170,000 - 240,000; Full time

Benefits offered by this job

Stock Options

Medical, Dental, and Vision insurance

401(k)

Flexible PTO

Parental Leave

Life Insurance

Disability Insurance

Pet & Legal Insurance

Flexible Spending Account

Employee Assistance Program

Paid Holidays

Other In-Office Perks

Job summary

TensorWave in the United States is seeking a Kubernetes Platform Staff Infrastructure Engineer to own the design, evolution, and reliability of our Kubernetes control plane across regions. You will drive multi-tenant cluster models, regional scaling, and on-call incident response, partnering with DevOps and Infrastructure teams to ensure CSP-grade reliability and secure, scalable workloads.

The role requires deep Kubernetes internals knowledge, Linux systems expertise, and experience operating

Qualifications

• 7+ years of experience in infrastructure or distributed systems.
• Deep experience operating Kubernetes at scale in production.
• Experience designing control plane architectures and multi-tenant clusters.
• Strong Linux systems expertise.

Responsibilities

• Own reliability and behavior of Kubernetes platforms in production.
• Lead incident response and participate in on-call rotation.
• Diagnose control plane instability and API server issues.
• Ensure lifecycle management across clusters: provisioning, upgrades, scaling.
• Collaborate with DevOps and Infrastructure teams to align platform design.

Skills

Kubernetes at scale

Linux systems

Networking

Observability

Multi-region platforms

Tools

Cilium

Kamaji

vcluster

Kubernetes dashboards

Job description

TensorWave in the United States is seeking a Kubernetes Platform Staff Infrastructure Engineer to own the design, evolution, and reliability of our Kubernetes control plane across regions. You will drive multi-tenant cluster models, regional scaling, and on-call incident response, partnering with DevOps and Infrastructure teams to ensure CSP-grade reliability and secure, scalable workloads.

The role requires deep Kubernetes internals knowledge, Linux systems expertise, and experience operating