AI Security Engineer, 2027 New Grad

Rebuild how the world works, to make institutions work better for the people they serve.

Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model.

Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services.

Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact.

You'll work alongside exceptional peers on some of the hardest problems in applied AI. It’s the kind of work you'll still be proud of in ten years from now.

As an AI Security Engineer, you'll build the tooling and automation that makes secure software the default at Brain Co. You'll work alongside security, platform, and infrastructure engineers — but your day-to-day is building.

This full-time, entry-level role is designed for candidates completing a bachelor's or master's degree in Spring 2027. You don't need prior security experience. You need to be someone who likes building things that work, and who's excited to use AI to automate problems that used to take a person. We'll teach you the security domain through code reviews, design discussions, pairing, and real ownership from day one.

• Build internal tools and automation that engineers across the company actually use — linters, reusable workflows, bots, CLIs, dashboards.

• Use AI and LLMs to automate work that previously required manual review: triaging findings, generating fixes, summarizing risk, writing remediation guidance.

• Add automated guardrails to CI/CD pipelines so problems get caught before they ship, instead of after.

• Write the automation that detects issues across cloud and infrastructure config, and — where possible — fixes them without a human in the loop.

• Turn noisy machine output into clear, actionable next steps for the engineers who have to act on it.

• Improve docs and developer experience so the safe path is also the fastest path.

• Participate in design reviews, code reviews, and architecture discussions as you ramp on the domain.

• 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, shown through internships, research, coursework, or personal projects.

• Write reliable code in Python, Go, Java, C++, Bash, or similar.

• Have shipped something someone else used — a tool, a script, a service, a side project.

• Have hands-on experience building with LLMs, or are eager to: prompting, agents, evals, or AI-assisted developer tooling.

• Have a working mental model of how code gets to production — version control, CI/CD, containers, cloud — even if you've never owned it professionally.

• Enjoy thinking about how systems fail and what could go wrong, and would rather prevent a problem than be paged for it.

• Are curious, proactive, and learn fast in a fast-moving environment.

• Want real ownership while learning from experienced engineers.

• 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 (AWS, GCP, Azure).

• Any prior security exposure including coursework, CTFs, bug bounties, research, or a security-adjacent internship.

• Curiosity about software supply chain security: dependencies, build integrity, provenance.