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San Francisco, California, United States
Onsite
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.
At Brain Co., new-grad engineers contribute to real production systems and see their work deployed at global scale.
As an AI Platform Engineer at Brain Co., you’ll help build the backend services and shared capabilities behind our AI products. You’ll solve technical problems, develop reliable software, and collaborate with Product and ML teams to bring AI applications to enterprise and government customers.
This full-time, entry-level role is designed for candidates completing a bachelor’s degree in Spring 2027. You’ll turn cutting-edge AI into systems that important institutions can depend on, taking ownership of clearly scoped projects involving APIs, distributed services, and developer tooling. You’ll work closely with experienced engineers, with support through code reviews, design discussions, and ongoing collaboration.
Design and build backend services and data pipelines that power Brain Co.’s AI products. Own scoped projects across implementation, testing, and maintenance, with guidance from experienced engineers.
Build tools that accelerate AI product development, including ML experiment tracking, artifact management, and automated training and evaluation pipelines.
Help build reliable systems for enterprise and government customers, with attention to testing and handling common failure cases.
Design modular, reusable components and clean APIs (REST, gRPC). Use profiling to improve application latency and throughput.
Partner with engineering, Product, and ML teams to build shared platform capabilities that remove bottlenecks and reduce the time it takes to ship new AI products.
Expect to complete a bachelor’s degree in Computer Science, Engineering, Machine Learning, Data Science, or a related field in Spring 2027.
Have solid foundations in data structures, algorithms, and databases, with familiarity with API design and testing.
Are comfortable writing and debugging code in at least one language such as Python, Go, TypeScript, Rust, Java, or C++.
Have built a backend service, API, data-intensive application, or developer tool through an internship, research, coursework, or a personal project.
Are curious about how systems work under the hood and eager to learn distributed-systems concepts such as consistency, failure handling, retries, and idempotency.
Care about building intuitive, well-documented, and maintainable APIs and shared tools for internal ML and product teams.
Enjoy breaking down open-ended problems into clear technical designs, reasoning from first principles, and communicating your ideas.
Take ownership of your work, care about its quality over time, and actively seek feedback and guidance when needed.
Eligibility: Completing a bachelor’s degree in Spring 2027.
Competitive full-time compensation and benefits
Support and feedback from experienced platform engineers
Opportunity to work on real production systems used globally
Meaningful ownership from day one, with room to grow alongside the team
Daily lunches (if onsite)
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