Kubernetes Engineer

Reposted 14 Days Ago
2 Locations
In-Office or Remote
100K-200K Annually
Junior
Artificial Intelligence • Machine Learning • Software • Infrastructure as a Service (IaaS)
The Role
Build and extend Kubernetes orchestration for AI inference: implement CRDs/controllers in Go, design high-performance ingress/load-balancing, implement GPU-aware autoscaling (HPA/VPA), tune scheduler/resource management, and ensure HA for platform components.
Summary Generated by Built In

About the company Tensormesh is building the next generation of AI inference infrastructure. Our mission is to make large language models faster, cheaper, and easier to deploy across any environment — cloud, on-prem, or hybrid. We help enterprises and AI teams optimize GPU utilization and scale inference workloads with up to 10× better performance.

About the role We are seeking a Kubernetes Engineer to build the core orchestration logic of the Tensormesh platform. Unlike a standard DevOps role, this position involves deep software development within the Kubernetes ecosystem. You will extend Kubernetes capabilities by writing custom operators and controllers that manage complex AI inference workloads, ensuring high availability and seamless auto-scaling.

What you’ll do

  • 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.

Ideal candidate credentials

  • 0-3 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.

Compensation & Benefits

  • Competitive base salary

  • Performance-based bonus

  • Equity options

  • Medical, dental, and vision insurance

  • 401(k) retirement plan

  • Paid time off

Why Join Tensormesh

  • Build infrastructure powering next-generation AI applications

  • Work alongside a highly technical and experienced engineering team

  • Make a direct impact in a fast-growing startup environment

  • Take ownership of challenging technical problems at scale

Skills Required

  • 0-3 years of software engineering experience focused on distributed systems or container orchestration
  • Strong proficiency in Go (Golang)
  • Experience developing Kubernetes operators/controllers and CRDs (using Golang/Kubebuilder or Operator SDK)
  • Familiarity with the Kubernetes client-go library
  • Deep understanding of Kubernetes internals (API machinery, Controller runtime, Networking, CNI)
  • Experience with GPU metrics, scheduler tuning, and autoscaling (HPA/VPA) for GPU workloads
  • Experience with service meshes (Istio, Linkerd) or ingress controllers (Nginx, Traefik)
  • Understanding of distributed consensus and state management
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The Company
Year Founded: 2025

What We Do

Tensormesh is an AI infrastructure optimization company that provides distributed AI compute infrastructure, including GPU clusters and inference optimization platforms, to reduce GPU costs and latency.

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