Create images, videos, and voice content with Higgsfield AI from text prompts or references. Edit and upscale media, automate creative workflows with its AI agent, and generate content on web and mobile. Backed by Accel and Menlo.
About the role
We're looking for a hands-on Infrastructure Security Engineer to own security across our cloud and ML infrastructure — the platform that trains our models and serves millions of generations a day. The work spans tenant isolation for user-deployed apps, GPU cluster security, and model protection from training pipeline to serving. You'll sit between Security, DevOps, and ML Engineering.
What they're looking for
- Few people will match all of these. If you're strong on some and eager to learn the rest, apply anyway
- 7+ years in infrastructure security or security engineering, including time at a high- growth startup
- 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
More about this role
Higgsfield AI is the fastest-scaling generative AI company in history, hitting $500M in annual revenue run rate, 25M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands.
We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like.
We're looking for a hands-on Infrastructure Security Engineer to own security across our cloud and ML infrastructure — the platform that trains our models and serves millions of generations a day.
The work spans tenant isolation for user-deployed apps, GPU cluster security, and model protection from training pipeline to serving. You'll sit between Security, DevOps, and ML Engineering.
You'll own both immediate implementation work and long-term operational responsibility: cloud and ML infrastructure security, vulnerability management, monitoring, and access governance.
We are looking for someone with experience in scaling high-growth startups who can make an immediate impact in the following...
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