AI Platform Engineer, Backend

Brain Co. is an applied AI startup co-founded by Jared Kushner and Elad Gil, and backed by leading Silicon Valley builders including Patrick Collison and Andrej Karpathy.

We are building AI applications for the world’s most important institutions, delivering impact on real-world problems across governments, healthcare systems, and critical industries.

Our progress so far:

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

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

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

Company momentum:

• Raised a $55M Series A from leading investors

• Built a team of 70+ AI experts from Tesla, Google DeepMind, NVIDIA, and Databricks

At Brain Co., we focus on applying frontier AI to real institutional challenges, working alongside governments, healthcare systems, and critical industries to modernize how essential services operate.

We are looking for leaders who want to help bring new technology into institutions that impact millions of people.

As a Backend Engineer at Brain Co., you'll own the systems that power our AI platform end-to-end, from architecture and design to deployment and maintenance. You'll build reliable, production-grade infrastructure for enterprise and government environments, solve complex problems from first principles, and work closely with teams across Product, ML, and Infrastructure. The work is meaningful: you'll be turning cutting-edge AI into systems that some of the world's most important organizations can actually depend on.

• Own it end-to-end: architecture, implementation, deployment, and long-term maintenance.

• Build for real environments, design modular, reusable APIs (REST, gRPC, event-driven) and backend architectures that meet enterprise and government uptime expectations.

• Think in first principles, break down complex, open-ended problems into clear technical designs and ship production-ready systems with speed and rigor.

• Optimize continuously, improve latency, throughput, and cost efficiency through profiling, thoughtful system design, and iteration.

• Partner closely with Product, ML, Infrastructure, and customer-facing teams, building systems that are intuitive, reliable, and developer-friendly.

• 3+ years building production systems with strong fundamentals in distributed systems (consistency, availability, failure modes, retries, idempotency) and deep proficiency in Go, TypeScript, Rust, Python, or similar.

• Proven ability to design from first principles, with experience building shared infrastructure, internal platforms, or developer-facing services and strong intuition for DX and long-term maintainability.

• Experience owning services with real uptime responsibility, plus familiarity with observability tooling (metrics, logging, tracing) and incident response.

• Track record designing, operating, and evolving APIs and services at scale.

• Experience with AI/ML platforms, inference systems, or data-intensive pipelines.

• Familiarity with Kubernetes and cloud-native service deployment.

• Exposure to multi-tenant, regulated, or government environments.

• Experience with real-time or streaming data systems.