FAL
Staff Security Engineer, Infrastructure
San Francisco · Staff+
Sponsorship not specifiedDetected 61 days ago
PythonGoFull-Stack DevelopmentAWSGCPAzureCloud PlatformsDockerKubernetesTerraformCI/CDLinuxSite Reliability EngineeringMachine LearningDesign SystemsZero TrustCommunicationCollaboration
About the role
- We're looking for a Security Engineer, Infrastructure to secure the core systems that power fal.ai's platform: GPU compute, multi-cloud environments, networking, and data pipelines.
- You'll operate across the full stack, from cloud and Kubernetes to identity, networking, and secrets, designing and implementing security controls that scale with a high-performance AI platform.
- This role is highly hands-on and systems-oriented, sitting at the intersection of security, infrastructure, and distributed systems.
Responsibilities
- Build & Harden Infrastructure Security
- Design and implement security controls across:
- Design secure data access pathways and isolation mechanisms
- Build security guardrails directly into infrastructure and CI/CD
- Drive projects like network isolation, encryption, and secure service communication
- Partner with platform, infra, and ML teams to drive shift-left security
- Assume breach, design for resilience
Requirements
- 8+ years in security engineering, infrastructure, or SRE
- Strong understanding of:
- Security Expertise
- Deep knowledge of:
- Proficiency in at least one language (Go, Python, or similar)
Nice to have
- Experience with:
- GPU infrastructure or ML systems
- Multi-tenant platform isolation
- Service mesh / zero-trust architectures
- High-growth startup environments
- What Makes This Role Unique
- Work on cutting-edge AI infrastructure security (not just SaaS)
- Secure GPU clusters, model execution, and real-time inference systems
Skills
- fal is the generative media ecosystem powering the next generation of AI products.
- Cloud infrastructure
- Kubernetes and containerized workloads
- Networking, service meshes, and edge systems
- CI/CD pipelines and deployment systems
- Secure compute environments for GPU workloads and model execution
- Machine identity and workload authentication
- Secrets management and encryption (e.g., Vault, KMS)
- Least-privilege access and short-lived credentials
- Implement Zero Trust principles across infrastructure
- Protect model weights, inference endpoints, and customer data
Compensation
- Competitive salary + equity
- Opportunity to work on frontier AI infrastructure
- You'll help define what security looks like for the next generation of AI infrastructure-where performance, scale, and safety all matter.
Benefits
- Competitive salary + equity
- Full health, dental, and vision coverage
- Opportunity to work on frontier AI infrastructure
This listing is sourced directly from FAL's careers page and normalized into a canonical job model.