Security Infra Engineer: Cloud & ML Lead (Hybrid)

Menlo Ventures; San Francisco (CA); Hybrid; USD 165,000 - 250,000; Full time

Benefits offered by this job

Equity

Hybrid work

Job summary

Higgsfield AI is the fastest-scaling generative AI company, building at the frontier of AI-powered video creation. We are looking for a hands-on Infrastructure Security Engineer to own security across cloud and ML infrastructure, partnering with Security, DevOps, and ML Engineering to protect models and data.

The role blends immediate security work with long-term operational responsibility, including vulnerability management, monitoring, and access governance.

Qualifications

• 7+ years in infrastructure security or security engineering at a high-growth startup.
• Deep hands-on experience securing AWS, Kubernetes, and using Terraform.
• Experience securing ML workloads — training or inference infrastructure, GPU clusters, or model-serving platforms.
• Strong 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.
• High agency.

Responsibilities

• Own cloud security tooling, vulnerability management, and network segmentation across cloud environments.
• Lead access governance and credential management across cloud and internal tooling.
• Set the technical direction for infrastructure security and drive cross-functional projects turning standards into tooling and guardrails.

Skills

Infrastructure security

Cloud security

Kubernetes

Terraform

Security engineering

Networking

Cross-functional collaboration

Security monitoring

Tools

AWS

Terraform

Job description

Higgsfield AI is the fastest-scaling generative AI company, building at the frontier of AI-powered video creation. We are looking for a hands-on Infrastructure Security Engineer to own security across cloud and ML infrastructure, partnering with Security, DevOps, and ML Engineering to protect models and data.

The role blends immediate security work with long-term operational responsibility, including vulnerability management, monitoring, and access governance.