Cloud & AI Infra Engineer for Agent Platform

Agentrys; San Jose (CA); Hybrid; USD 140,000 - 180,000; Full time

Job summary

Agentrys is seeking an Infrastructure Engineer to design and operate the platform behind our agentic design‑automation systems, spanning multi‑cloud infrastructure and on‑prem, private‑cloud, and air‑gapped environments.

You will own the Kubernetes/container foundation, build enterprise security end‑to‑end, and scale AI/ML infrastructure, GPU clusters, and data pipelines to support diverse customer deployments.

Qualifications

• Experience operating production infrastructure on a major cloud (GCP, AWS, or Azure).
• Expert Kubernetes and container skills (Docker/OCI, Helm).
• Proven track record delivering software into on‑prem, private‑cloud, or air‑gapped environments.
• Strong enterprise security—RBAC/ReBAC, identity/SSO, secrets, and audit.
• Proficiency in Go, Node, Python, or Rust and infrastructure‑as‑code (Terraform).
• CI/CD and artifact/release management experience.

Responsibilities

• Architect and operate multi‑cloud infra across GCP, AWS, and Azure.
• Design on‑prem/private‑cloud deployments, including air‑gapped environments.
• Own Kubernetes/container foundation: cluster, autoscaling, multi‑tenancy, upgrades.
• Build enterprise access and security end‑to‑end: RBAC/ReBAC, SSO, secrets, audit.
• Develop compute infra for EDA workloads within the Agentrys fabric.
• Scale AI/ML infra: GPU clusters, scheduling, model serving & env management.
• Create data/artifact pipelines and release processes for cloud/on‑prem/a/gapped customers.

Skills

Cloud infra ops

Kubernetes

Containerization

On‑prem/private‑cloud

RBAC/ReBAC security

Go/Node/Python/Rust

Terraform

CI/CD

Tools

Docker

Helm

Terraform

Job description

Agentrys is seeking an Infrastructure Engineer to design and operate the platform behind our agentic design‑automation systems, spanning multi‑cloud infrastructure and on‑prem, private‑cloud, and air‑gapped environments.

You will own the Kubernetes/container foundation, build enterprise security end‑to‑end, and scale AI/ML infrastructure, GPU clusters, and data pipelines to support diverse customer deployments.