Security Infrastructure Engineer

Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ 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.

Higgsfield AI is looking for a hands-on Infrastructure Security Engineer to own security across our cloud infrastructure, GPU environments, and machine learning platforms.

As we scale to support millions of AI generations daily, you'll play a critical role in securing the infrastructure powering model training, inference, and customer-facing applications.

Working closely with Infrastructure, DevOps, and ML Engineering, you'll identify security risks, implement technical controls, and establish scalable security practices. This role combines hands-on engineering with technical ownership, from securing GPU workloads and cloud environments to strengthening access governance, vulnerability management, and threat detection.

We're looking for someone who thrives in fast-moving environments, takes ownership of complex challenges, and builds security solutions without slowing engineering velocity.

• Design, implement, and maintain security controls across cloud infrastructure, Kubernetes environments, and GPU clusters.

• Own infrastructure and container vulnerability management, including assessment, prioritization, and remediation.

• Implement network segmentation, workload isolation, and secure infrastructure configurations.

• Evaluate and deploy cloud security tooling, including CSPM solutions, and build centralized security monitoring.

• Embed security controls into CI/CD pipelines, infrastructure-as-code, and deployment workflows.

• Secure ML training, inference, and model-serving infrastructure, including GPU workloads and distributed compute environments.

• Protect model weights, checkpoints, sensitive datasets, and customer inputs and outputs.

• Strengthen tenant isolation and workload security across shared infrastructure and customer-facing applications.

• Partner with ML Engineering and Platform teams to identify risks and implement scalable security controls.

• Own access governance, credential management, and privileged access controls across cloud and engineering systems.

• Implement least-privilege access, secrets management, and auditable authentication practices.

• Build monitoring and detection capabilities to identify and respond to infrastructure security threats.

• Partner with Engineering, DevOps, and IT to strengthen security standards and operational practices.

• Define and execute an infrastructure security roadmap aligned with engineering priorities and business growth.

• Lead security initiatives from technical design through implementation and ongoing operations.

• Conduct threat modeling and security reviews to proactively identify and mitigate risks.

• Translate security requirements into practical tooling, automation, and engineering guardrails.

• 7+ years of experience in infrastructure security, cloud security, or security engineering, ideally within a high-growth technology startup.

• Deep hands-on experience securing cloud platforms (AWS preferred), Kubernetes environments, and infrastructure managed through Terraform.

• Experience securing ML infrastructure, including training or inference workloads, GPU clusters, or model-serving platforms.

• Strong understanding of networking, Linux, container security, and cryptography fundamentals.

• Proven experience with vulnerability management, cloud security tooling, and infrastructure security controls.

• Familiarity with identity and access management, secrets management, and least-privilege principles.

• Ability to independently identify, prioritize, and resolve complex security challenges.

• Strong cross-functional collaboration skills and a high degree of ownership in fast-paced environments.

• We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth.

• Base Salary: The anticipated salary range for this role is $200,000 - $300,000, depending on experience, skills, scope, and location.

• Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. •

• Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally

• The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team.

• Significant ownership, direct impact, and opportunities for professional growth as the company scales.

This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams.

Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.