AI Platform Engineer Intern (Summer 2027)

Brain Co.•San Francisco, CA

59d

About The Position

Brain Co. is hiring an AI Platform Engineer Intern to work with engineers across Product, ML, and Infrastructure on backend services and platform capabilities for its AI applications. The intern will contribute to APIs, shared services, developer tooling, and production systems used in enterprise and government environments. The internship is intended for current undergraduate juniors and seniors graduating no later than June 2028 who want hands-on experience building production software. The intern will take on scoped projects across backend systems, distributed services, AI/ML platform integrations, reliability, and developer experience, with mentorship through code reviews, design discussions, and hands-on collaboration. Work is expected to progress from technical design through implementation, testing, deployment, and maintenance, and may be deployed to real users.

Requirements

Be a current undergraduate junior or senior graduating no later than June 2028.
Be pursuing a degree in Computer Science, Engineering, or a related technical field.
Have strong foundations in data structures, algorithms, object-oriented programming, systems, and databases.
Have experience building software in Go, TypeScript, Rust, Python, Java, C++, or a similar language.
Have built a backend service, API, data-intensive application, or developer tool through coursework, an internship, research, or a personal project.
Be comfortable with Git, testing, and debugging.
Enjoy breaking down ambiguous problems from first principles and communicating an approach clearly.
Be curious, proactive, and excited to own technical problems while seeking feedback when needed.

Nice To Haves

Understand, or be eager to learn, API design, databases, distributed systems, and reliability concepts.
Be interested in cloud or containerized deployment.

Responsibilities

Build and improve backend services and APIs, including REST, gRPC, and event-driven systems, that power AI applications and shared platform capabilities.
Take scoped features from technical design through implementation, testing, deployment, and maintenance.
Develop modular, reusable platform components and developer-facing tooling to help teams build and ship reliably.
Work with databases, queues, caches, and distributed systems, including consistency, retries, idempotency, and failure modes.
Improve latency, throughput, reliability, and cost through profiling, observability, and system design.
Contribute to systems supporting AI inference, data pipelines, and customer-facing workflows.
Partner with Product, ML, Infrastructure, and customer-facing teams to translate open-ended needs into technical solutions.
Participate in code reviews, architecture discussions, and technical problem-solving.