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Kubernetes Engineer

Tensormesh
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Hybrid (Foster City, CA)$100k - $200kFull-timePosted 3mo ago

About the role

Kubernetes Engineer role at Tensormesh building core orchestration logic for AI inference infrastructure, extending Kubernetes with custom operators/controllers to manage complex AI workloads, with emphasis on high availability, auto-scaling, and GPU utilization.

Responsibilities

  • Develop Custom Operators: Design and implement Kubernetes Custom Resource Definitions (CRDs) and Controllers (using Golang/Kubebuilder) to manage the lifecycle of Tensormesh products.
  • Traffic Management: Architect and build high-performance ingress and load-balancing systems capable of handling high-throughput inference requests.
  • Resilience & Scaling: Develop logic for intelligent auto-scaling (HPA/VPA) based on GPU metrics and ensure High Availability (HA) for critical components.
  • K8s Optimization: Tune the scheduler and resource management configurations to maximize GPU utilization for inference tasks.

Qualifications

  • 2-10 years of software engineering experience, with a focus on distributed systems or container orchestration.
  • Strong proficiency in Go (Golang); experience with the Kubernetes client-go library and Kubebuilder/Operator SDK is highly preferred.
  • Deep understanding of Kubernetes internals (API machinery, Controller runtime, Networking, CNI).
  • Experience with service meshes (Istio, Linkerd) or ingress controllers (Nginx, Traefik) is a plus.
  • Understanding of distributed consensus and state management.

Skills

Required:Go (Golang)KubernetesCustom Resource Definitions (CRDs)
Nice to have:Kubebuilder/Operator SDK

Benefits

  • Competitive base salary
  • Performance-based bonus
  • Equity options
  • Medical, dental, and vision insurance
  • 401(k) retirement plan
  • Paid time off
Last updated Aug 23, 2026. Interested? Apply on the company site.

About Tensormesh

Cached tokens

Tensormesh caches repeated prompts, documents, tools, and workflow context, helping your AI apps run faster and cheaper with $0 cached tokens.

AI InferenceCachingCloud/InfrastuctureContext CachingCost ReductionOpenAI-Compatible APIReservedServerless
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