About the role
Why work at Higgsfield AI? 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. Role Overview 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. Key
Responsibilities We are looking for someone with experience in scaling high-growth startups who can make an immediate impact in the following areas: Cloud & Network Security Evaluate, implement, and maintain cloud security tooling. Own infrastructure and container vulnerability management across our cloud environments, and drive remediation. Design and implement network segmentation to tighten internal security boundaries. Build centralized security monitoring across cloud infrastructure. Corporate Access Control Own access governance and credential management across cloud and internal tooling. Partner with Engineering, DevOps, and IT to raise identity and access management standards. Technical Leadership: Set the technical direction for infrastructure security and lead cross-functional projects turning the standards you set into tooling and guardrails engineers actually ship with.
Requirements: 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. Comfortable working cross-functionally with DevOps, Engineering, and ML teams; able to independently find and close security gaps. High agency.
