# Member of Technical Staff - Infrastructure Security at Black Forest Labs

Black Forest Labs is hiring a Member of Technical Staff - Infrastructure Security. It pays $220k-$280k a year and Level rates it Builds AI ●●●●; you can [apply on Black Forest Labs](https://jobsbylevel.com/go/238c59ce-635e-407b-8e2b-f0aaf8e0f681?utm_medium=ai-agent).

AI Level 4, AI centrality 85 out of 100. Remote (San Francisco (United States)).

## Details

- Company: [Black Forest Labs](https://jobsbylevel.com/companies/black-forest-labs)
- AI level: AI Level 4 (score 85 out of 100)
- Location: Remote (San Francisco (United States))
- Salary: $220k-$280k
- Posted: November 15, 2026
- Apply: https://jobsbylevel.com/go/238c59ce-635e-407b-8e2b-f0aaf8e0f681?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=member-of-technical-staff-infrastructure-security-at-black-forest-labs-fec8b2

## Prepare for this job

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## Description

About Black Forest Labs We’re the team building the foundational layer for visual intelligence: multimodal models trained jointly on images, video, audio, and action to see, generate, and understand the world. Our founding team pioneered latent diffusion and Stable Diffusion, the breakthroughs that made generative AI accessible to millions. With FLUX, we're pushing into generative media at scale, machines that act in the physical world, and emerging applications in computer use. Our FLUX models top public benchmarks and run in production in some of the world's biggest platforms. We're a small, fast growing research lab competing with the largest companies in the world. From our labs in Freiburg to San Francisco, we're building what comes next. Why This Role We develop AI models and run the infrastructure on which those models are trained, deployed, and served to customers. Securing that infrastructure comes with real challenges: researchers need flexible access to significant compute resources, production systems need strong isolation and reliability, and model assets and customer data need protection throughout their lifecycle. Our research and production infrastructure teams design, build, and operate these systems. We're looking for an experienced, hands-on security engineer to partner with them as we grow: someone who can dig into the details, do the engineering, and work alongside those teams to improve our defensive posture. This is an engineering role: you'll spend time reading code, understanding systems, debugging problems, and shipping changes. What You’ll Work On These are the areas this role draws from; you're not expected to cover them all at once: Infrastructure architecture and isolation. Understand how our research and production environments fit together, identify consequential attack paths, and work with infrastructure teams to improve network boundaries, workload isolation, and access controls. Identity and access. Improve how people, services, and workloads authenticate and obtain access to infrastructure. Reduce unnecessary privileges, strengthen secrets management, and develop practical approaches to short-lived credentials and privileged access. Cloud and compute security. Strengthen security across cloud infrastructure, compute clusters, containers, storage, and orchestration systems. Help establish reusable patterns that engineers can adopt without unnecessary friction. Model and customer-data protection. Work with research and engineering teams to protect model artifacts, training and inference pipelines, and sensitive data. Understand where trust boundaries matter and develop ways to verify that they hold. Security in engineering workflows. Improve the security of infrastructure-as-code, build and deployment pipelines, and software artifacts. Build tooling and guardrails that help engineering teams prevent, detect, and fix problems without making security a bottleneck. What We’re Looking For Strong experience securing production cloud infrastructure, with a solid understanding of identity, networking, operating systems, and distributed systems. Hands-on engineering ability. You can write and review code, work with infrastructure-as-code, debug unfamiliar systems, and implement the improvements you recommend. Good security judgment. You can distinguish meaningful risks from theoretical ones, make sensible tradeoffs, and explain why a particular security improvement matters. Experience working closely with infrastructure or platform engineers, including designing changes that are practical to deploy and operate. Experience in using LLMs and agents for security work, along with a clear-eyed view of where they help, where they don't, and how they themselves can be attacked. Comfort working with real autonomy, finding your way through complex systems, and turning loosely defined problems into concrete improvements. Experience with GPU clusters, ML infrastructure, multi-tenant services, Kubernetes, and

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