Security Engineer

Cerebro; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity

Benefits package

Job summary

Cerebro in San Francisco is seeking a Security Engineer to design and operate security across frontier AI infrastructure. You will own security architecture for distributed GPU clusters, protect model weights and datasets, and embed security into pipelines and orchestration systems like Kubernetes and Slurm.

The role requires hands-on software and systems engineering, cloud experience, and the ability to move from risk identification to implementation.

Qualifications

• Strong experience in infrastructure, platform, cloud or product security.
• Fluency across Linux, networking, cloud infrastructure and infrastructure-as-code.
• Strong programming ability in Python, Go, Rust or a comparable language.
• Experience with AWS, GCP or Azure and modern containerised infrastructure.
• Knowledge of IAM, encryption, secrets management, threat modelling and incident response.
• The ability to independently move from identifying a risk to designing, implementing and operating the solution.
• Ideally, experience securing ML platforms, distributed systems, GPU infrastructure or high-value technical IP.

Responsibilities

• Security architecture across distributed GPU clusters, shared compute platforms and network infrastructure.
• Identity, authentication and access controls protecting researchers, datasets and model checkpoints.
• Data governance and encryption for petabyte-scale physical observations and valuable proprietary IP.
• Security embedded directly into research pipelines, APIs and orchestration systems including Kubernetes and Slurm.
• Threat modelling, architectural reviews and vulnerability assessments across rapidly evolving systems.
• Detection and incident-response capabilities designed specifically for large-scale ML infrastructure.
• Security requirements for customer deployments across cloud, VPC, on-premise and restricted environments.
• Pragmatic controls that protect critical assets without slowing down research.

Skills

Infrastructure security

Linux

Networking

Cloud infrastructure

Kubernetes

Python

Go

Rust

IAM

Encryption

Threat modelling

Incident response

Tools

Slurm

AWS

GCP

Azure

Job description

Security Engineer — Frontier AI Infrastructure

Most security engineers protect conventional applications.

This role protects distributed GPU clusters, proprietary model weights, petabyte-scale scientific datasets and the infrastructure behind a new class of frontier AI model.

We’re representing a well‑capitalised San Francisco research lab developing foundation models capable of understanding and predicting complex physical systems. Its founding team brings experience from some of the world’s leading AI, autonomous‑systems and scientific research organisations.

The lab is now making a foundational security hire to design and operate its security posture across the entire engineering stack.

What you’ll own

• Security architecture across distributed GPU clusters, shared compute platforms and network infrastructure.
• Identity, authentication and access controls protecting researchers, datasets and model checkpoints.
• Data governance and encryption for petabyte-scale physical observations and valuable proprietary IP.
• Security embedded directly into research pipelines, APIs and orchestration systems including Kubernetes and Slurm.
• Threat modelling, architectural reviews and vulnerability assessments across rapidly evolving systems.
• Detection and incident-response capabilities designed specifically for large‑scale ML infrastructure.
• Security requirements for customer deployments across cloud, VPC, on‑premise and restricted environments.
• Pragmatic controls that protect critical assets without slowing down research.

What we’re looking for

• Strong experience in infrastructure, platform, cloud or product security.
• A genuine software and systems engineering background—not solely governance, compliance or security operations.
• Fluency across Linux, networking, cloud infrastructure and infrastructure-as-code.
• Strong programming ability in Python, Go, Rust or a comparable language.
• Experience with AWS, GCP or Azure and modern containerised infrastructure.
• Knowledge of IAM, encryption, secrets management, threat modelling and incident response.
• The ability to independently move from identifying a risk to designing, implementing and operating the solution.
• Ideally, experience securing ML platforms, distributed systems, GPU infrastructure or high‑value technical IP.

Why consider it?

You won’t inherit a narrow corner of an established security programme.

You’ll work directly with research and infrastructure engineers, shape security architecture while the platform is still being built, and protect systems operating at the frontier of AI and the physical sciences.

This is a rare opportunity for a security engineer who wants genuine technical ownership, difficult systems problems and direct influence over how a frontier research organisation scales.

Competitive cash compensation, meaningful equity and comprehensive benefits are offered.