Senior AI Cloud Kubernetes Engineer

Lambda Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Wellness and commuter stipends

401k Plan with 2% company match

Flexible paid time off

Job summary

Lambda Inc. in the San Francisco Bay Area is seeking a Senior Software Engineer to join the Mk8s team.

You will design and build scalable control plane services, Kubernetes operators, and GPU-aware orchestration that powers AI workloads across a distributed platform. As part of the Orchestration team, you will work on managed Kubernetes, Slurm on Kubernetes, and platform services for inference, while collaborating across stacks to deliver reliable, high-performance systems.

Qualifications

• 6+ years of software engineering experience with ownership of significant technical scope.
• Deep understanding of Kubernetes internals: controllers, schedulers, operators, CRDs, CSI, CNI, and extension patterns.
• Strong grasp of distributed systems: fault tolerance and large-scale failure handling.
• Experience with observability tooling (Prometheus, Grafana) and distributed tracing.
• Proficiency in Go and Python; collaboration on shared codebases.

Responsibilities

• Design, build, and maintain scalable control plane services and Kubernetes controllers; automate end-to-end cluster lifecycle management in Go/Python.
• Build GPU-aware orchestration systems to support GPU scheduling and resource allocation.
• Collaborate on networking solutions for AI workloads (CNI, InfiniBand, RDMA).
• Write resilient systems with timeouts, retries, and degraded-mode operation across large-scale environments.
• Develop platform services for inference, including model serving and autoscaling.

Skills

Kubernetes

Distributed systems

Go

Python

Linux

Tools

Prometheus

Grafana

Job description

Lambda Inc. in the San Francisco Bay Area is seeking a Senior Software Engineer to join the Mk8s team.

You will design and build scalable control plane services, Kubernetes operators, and GPU-aware orchestration that powers AI workloads across a distributed platform. As part of the Orchestration team, you will work on managed Kubernetes, Slurm on Kubernetes, and platform services for inference, while collaborating across stacks to deliver reliable, high-performance systems.