Senior Staff Infrastructure Engineer – Kubernetes Platform

Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.

We’re looking for a Kubernetes Platform Staff Infrastructure Engineer to join our team during an exciting phase of growth. In this role, you’ll be responsible for owning the design, evolution, and operational reliability of our Kubernetes control plane architecture, working closely with cross-functional partners to support business objectives while upholding our standards for excellence, collaboration, and impact.

• Design and evolve Kubernetes control plane architecture across regions

• Define and implement multi-tenant cluster models, including shared control planes, virtual cluster approaches (e.g., vcluster, Kamaji)

• Drive transition from standalone clusters to regionally managed platform models

• Define standards for isolation boundaries, resource segmentation, policy enforcement

• Own the reliability and behavior of Kubernetes platforms in production

• Participate in on-call rotation and lead incident response

• Diagnose and resolve control plane instability, API server saturation, scheduling and resource contention issues

• Ensure consistent lifecycle management across clusters - provisioning, upgrades, scaling

• Design and implement strategies for regional scaling, multi-data center cluster deployments

• Ensure consistent behavior and reliability across environments

• Define cluster topology and failure domain strategies

• Design ingress and egress architectures at cluster level and regional level

• Troubleshoot and optimize pod-to-pod networking, north-south traffic flows, CNI behavior (Cilium preferred)

• Collaborate with network engineering on high-performance networking integration

• Improve observability across control plane components, cluster health and performance

• Define and implement resilience strategies aligned with platform goals

• Lead root cause analysis for production incidents

• Work closely with DevOps engineers (automation and CI/CD) and Infrastructure teams (compute, storage, networking)

• Align Kubernetes platform design with underlying infrastructure capabilities

• 7+ years of experience in infrastructure, platform engineering, or distributed systems

• Deep experience operating Kubernetes at scale in production environments

• Experience in CSP, hyperscale, or equivalent large-scale environments strongly preferred

• Proven experience scaling Kubernetes across:

  • Multiple clusters

  • Multiple regions or data centers

• Strong understanding of Kubernetes internals:

  • API server

  • Scheduler

  • Controller manager

  • etcd

• Experience designing or evolving:

  • Control plane architectures

  • Multi-tenant cluster models

• Experience with virtual cluster technologies (vcluster, Kamaji, or similar)

• Experience supporting GPU workloads in Kubernetes

• Familiarity with:

  • NUMA-aware scheduling

  • Topology-aware workloads

• Awareness of RDMA and high-throughput networking environments

• Experience with observability platforms (Prometheus, Grafana, etc.)

• Strong Linux systems expertise

• Deep troubleshooting ability across:

  • Kubernetes

  • Container runtime

  • Networking stack

• Experience with CNI plugins (Cilium preferred)

• Strong understanding of:

  • Networking and traffic patterns

  • Resource isolation and scheduling

TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.

TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact accomodations@tensorwave.com.

All offers of employment are contingent upon verification of identity and authorization to work in the United States, as required by law.

Where permitted by law, employment may be contingent upon the successful completion of a job-related background check.

By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.