AI Security Engineer, 2027 New Grad

Brain Co.•San Francisco, CA

38d

About The Position

Brain Co. is hiring an entry-level AI Security Engineer to build tooling and automation that makes secure software the default. The engineer will work alongside security, platform, and infrastructure engineers, with a day-to-day focus on building. The role is intended for candidates completing a bachelor's or master's degree in Spring 2027; prior security experience is not required. Security knowledge will be developed through code reviews, design discussions, pairing, and ownership from day one. The engineer will build internal tools, use AI and LLMs to automate security work, add guardrails to CI/CD pipelines, and develop automation to detect and, where possible, fix issues in cloud and infrastructure configuration. The role also involves translating machine-generated findings into actionable guidance, improving documentation and developer experience, and participating in design, code, and architecture reviews. Brain Co. builds AI-native operating systems for regulated institutions, powered by agents and its Atlas platform. The company describes this role as an opportunity to work on production systems and deliver measurable customer value, with meaningful ownership and support from experienced security and infrastructure engineers.

Requirements

Expect to complete a bachelor's or master's degree in Computer Science, Engineering, or a related technical field in Spring 2027.
Have strong software engineering fundamentals demonstrated through internships, research, coursework, or personal projects.
Write reliable code in Python, Go, Java, C++, Bash, or a similar language.
Have shipped a tool, script, service, side project, or other work that someone else used.
Have hands-on experience building with LLMs or be eager to work with prompting, agents, evaluations, or AI-assisted developer tooling.
Have a working mental model of how code reaches production, including version control, CI/CD, containers, and cloud.
Be curious, proactive, and able to learn quickly in a fast-moving environment.
Want real ownership while learning from experienced engineers.

Nice To Haves

Projects or internships involving developer tools, platform engineering, or internal automation.
Experience building with AI/LLM APIs, agent frameworks, or evaluation pipelines.
Exposure to Kubernetes, Docker, Terraform, GitHub Actions, or a major cloud provider such as AWS, GCP, or Azure.
Prior security exposure through coursework, CTFs, bug bounties, research, or a security-adjacent internship.
Curiosity about software supply chain security, including dependencies, build integrity, and provenance.

Responsibilities

Build internal tools and automation used by engineers, such as linters, reusable workflows, bots, CLIs, and dashboards.
Use AI and LLMs to automate tasks previously requiring manual review, including triaging findings, generating fixes, summarizing risk, and writing remediation guidance.
Add automated guardrails to CI/CD pipelines to catch problems before they ship.
Develop automation to detect issues across cloud and infrastructure configuration and, where possible, fix them without human intervention.
Turn machine output into clear, actionable next steps for engineers.
Improve documentation and developer experience so that the safe path is also the fastest path.
Participate in design reviews, code reviews, and architecture discussions while learning the security domain.