Infrastructure Engineer

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

I’m working with a highly technical AI and semiconductor startup building autonomous agents capable of carrying out complex chip-design workflows.

They are hiring an Infrastructure Engineer to build the platform through which those agents operate across internal cloud infrastructure and customer-managed environments.

You will work across:

• Multi-cloud infrastructure spanning AWS, GCP and Azure
• Kubernetes, containers, Helm, autoscaling and multi-tenancy
• On-premises, private-cloud and air-gapped deployments
• Enterprise identity, authorization, secrets and auditing
• GPU infrastructure for distributed training and inference
• EDA compute environments, workload scheduling and isolation
• CI/CD, artifact management and secure software distribution

We are looking for someone with strong Kubernetes and production-cloud experience who has also delivered software into complex enterprise or customer-controlled environments.

Experience with GPU clusters, Slurm, LSF, EDA infrastructure, high-performance networking or offline deployment packages would be particularly valuable.

This is an opportunity to build the infrastructure connecting modern AI agents with real semiconductor-engineering tools and workflows from an early stage.