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Brain Co.

AI Platform Engineer Intern (Summer 2027)

Posted 8 Days Ago
Remote or Hybrid
Hiring Remotely in CA
Internship
Remote or Hybrid
Hiring Remotely in CA
Internship
Interns build backend services, APIs, distributed systems, platform components, developer tools, and AI/ML infrastructure. Responsibilities span design, implementation, testing, deployment, maintenance, reliability, performance optimization, observability, and collaboration with Product, ML, Infrastructure, and customer-facing teams. The role is intended for undergraduate juniors and seniors graduating by June 2028 and offers mentorship through production-focused engineering work.
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Our Mission

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

About Brain Co.

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.

Why Now

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.

About Brain Co.

Brain Co. is an applied AI startup founded by Elad Gil and Jared Kushner, backed by many of Silicon Valley’s leading builders, including Patrick Collison (CEO of Stripe), Andrej Karpathy (Cofounder of OpenAI), Mike Krieger (CPO of Anthropic), Kevin Weil (CPO of OpenAI), and Aravind Srinivas (CEO of Perplexity).

We build AI platforms and applications for the world’s most important institutions, delivering real impact on complex, real-world problems.

Our progress so far:

  • Automated construction permitting for a sovereign government → 80% faster, unlocking $375M+ in value

  • Optimized supply chains for a global energy leader → 30% lower cost, 99% reliability, preventing $100M+ in losses

  • Streamlined hospital patient care across national health systems → 40% better outcomes, 80% less admin work

  • Raised a $30M Series A from top-tier investors

  • Built a team of 40+ AI experts from Tesla, Google DeepMind, NVIDIA, and Databricks

At Brain Co., co-op interns contribute to real production systems and see their work deployed at global scale.

About the Role

As an AI Platform Engineer Intern, you’ll work alongside engineers across Product, ML, and Infrastructure to build the backend services and platform capabilities that power Brain Co.’s AI applications. You’ll contribute to APIs, shared services, developer tooling, and production systems used in enterprise and government environments.

This internship is designed for current undergraduate students, specifically juniors and seniors graduating no later than June 2028, who want hands-on experience building real production software. You’ll 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 with the team.

What You’ll Work On
  • 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 that help teams build and ship reliably.

  • Work with databases, queues, caches, and distributed systems, learning how to handle consistency, retries, idempotency, and failure modes.

  • Improve latency, throughput, reliability, and cost through profiling, observability, and thoughtful system design.

  • Contribute to systems that support AI inference, data pipelines, and customer-facing workflows.

  • Partner with Product, ML, Infrastructure, and customer-facing teams to translate open-ended needs into clear technical solutions.

  • Participate in code reviews, architecture discussions, and technical problem-solving, and see your work deployed to real users.

You Might Be a Great Fit If You…
  • Are a current undergraduate junior or senior graduating no later than June 2028 and 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.

  • Understand—or are eager to learn—API design, databases, distributed systems, and reliability concepts.

  • Are comfortable with Git, testing, and debugging, and are interested in cloud or containerized deployment.

  • Enjoy breaking down ambiguous problems from first principles and communicating your approach clearly.

  • Are curious, proactive, and excited to own technical problems while seeking feedback when needed.

Internship Details & Benefits
  • Dates: May 31, 2027 - Aug 6, 2027 or July 5, 2027 - September 10, 2027

  • Competitive internship compensation

  • Hands-on mentorship from experienced AI engineers and researchers

  • Opportunity to work on real production systems used globally

  • Potential return-offer consideration for future internships or full-time roles

  • Daily lunches (if onsite)

Compensation

The base salary range for this internship role is $8,000-10,000 per month plus a stipend for housing. We publish this range for every internship role, as a matter of policy regardless of whether local law requires it. Actual pay will depend on scope, skills, experience.

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