Hybrid Security Infrastructure Engineer — AI Cloud & ML

Higgsfield Inc.; San Francisco (CA); Hybrid; USD 165,000 - 187,000; Full time

Benefits offered by this job

Stock options

Hybrid work model

Competitive compensation

Job summary

Higgsfield AI in the San Francisco Bay Area is seeking an experienced Infrastructure Security Engineer to own security across our cloud and ML infrastructure, including GPU clusters and model serving environments.

You will work between Security, DevOps, and ML Engineering, own vulnerability management and access governance, and help scale security as the company grows in a high-impact, fast-moving startup.

Qualifications

• 7+ years in infrastructure security or security engineering.
• Deep hands-on experience securing a major cloud provider and a container orchestrator, managed with infrastructure-as-code (AWS, Kubernetes, Terraform).
• Experience securing ML workloads — training or inference infrastructure, GPU clusters, or model-serving platforms.
• Solid networking, operating systems, and cryptography fundamentals.
• Strong grasp of container and infrastructure security practices and vulnerability management.
• Comfortable working cross-functionally with DevOps, Engineering, and ML teams; able to independently find and close security gaps.

Responsibilities

• Own cloud & network security tooling and remediation across cloud environments.
• Lead access governance and credential management across cloud and internal tooling.
• Set technical direction for infrastructure security and drive cross-functional projects into tooling and guardrails.

Skills

Cloud security

Container security

Vulnerability management

Networking fundamentals

Cryptography fundamentals

Cross-functional collaboration

High agency

Tools

AWS

Kubernetes

Terraform

Job description

Higgsfield AI in the San Francisco Bay Area is seeking an experienced Infrastructure Security Engineer to own security across our cloud and ML infrastructure, including GPU clusters and model serving environments.

You will work between Security, DevOps, and ML Engineering, own vulnerability management and access governance, and help scale security as the company grows in a high-impact, fast-moving startup.