Kubernetes Infra Engineer for AI & Chip Workflows

Oho Group; San Francisco (CA); On-site; USD 130,000 - 170,000; Full time

Job summary

Oho Group is hiring an Infrastructure Engineer to build the platform powering autonomous AI agents across cloud and customer-managed environments in the San Francisco Bay Area.

You will manage multi-cloud Kubernetes-based infrastructure, on-prem and air-gapped deployments, GPU clusters for training and inference, and Enterprise IAM, secrets and auditing, while integrating CI/CD and secure software distribution into complex enterprise workflows.

Qualifications

• Experience running production Kubernetes clusters in multi-cloud environments.
• Deployed on-premises/private-cloud and air-gapped deployments.
• Strong CI/CD, artifact management and secure software distribution.
• Experience with enterprise identity, authorization, secrets and auditing.
• GPU infrastructure experience for training/inference.
• Familiar with Slurm or LSF and EDA compute workflows.

Responsibilities

• Build the platform powering autonomous AI agents across cloud and customer-managed environments.
• Manage multi-cloud infrastructure (AWS, GCP, Azure) and on-prem/private-cloud setups.
• Implement Kubernetes, containers, Helm, autoscaling and multi-tenancy.
• Oversee enterprise identity, secrets and auditing.
• Support GPU clusters for distributed training and inference.
• Integrate CI/CD and secure software distribution into enterprise workflows.

Skills

Kubernetes

Containerization

Autoscaling

Multi-tenancy

Security and auditing

Identity and access management

CI/CD

On-premises deployments

Private cloud deployments

Offline deployment packages

High-performance networking

Tools

AWS

GCP

Azure

Helm

Slurm

LSF

GPU clusters

EDA infrastructure tooling

Job description

Oho Group is hiring an Infrastructure Engineer to build the platform powering autonomous AI agents across cloud and customer-managed environments in the San Francisco Bay Area.

You will manage multi-cloud Kubernetes-based infrastructure, on-prem and air-gapped deployments, GPU clusters for training and inference, and Enterprise IAM, secrets and auditing, while integrating CI/CD and secure software distribution into complex enterprise workflows.