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 core backend engineer at Brain Co., you will build the shared technical capabilities that help us scale our AI products quickly, safely, and reliably. You will take ambiguous product and technical challenges, turn them into clear system designs, and ship robust platforms that support real-world AI applications for the world’s most important institutions. If you are driven by high-stakes engineering and thrive on delivering systems built for uncompromising reliability, this is the exact opportunity for you.
Design, build, and operate the platform backend services and data pipelines that power Brain Co.'s AI products. You will own the full lifecycle: from initial architecture and implementation to deployment and long-term maintenance.
Build the critical systems that accelerate our AI product development. This includes designing scalable solutions for ML experiment tracking, artifact management, and automated training and evaluation pipelines.
Engineer highly available, fault-tolerant systems with deep observability. Your architectures must be robust enough to meet the strict uptime and latency SLAs demanded by our enterprise and government clients.
Design modular and scalable architectures, and clean APIs (REST, gRPC) with a long-term platform mindset. Continuously profile systems to ruthlessly optimize for latency, throughput, and cloud compute costs.
Act as the bridge between engineering, product, and ML research. You will partner with these teams to build shared platform capabilities that remove bottlenecks and drastically reduce the time it takes to ship new AI products to our clients.
You bring 3+ years of experience building and scaling production backend services or platforms, ideally using languages common in the AI/Data ecosystem (e.g., Python, Go, Rust, or C++).
You don't just use frameworks; you understand what happens under the hood. You have a deep grasp of consistency, availability, distributed failure modes, and idempotency.
You treat our internal ML and product teams as your primary customers. You have a strong intuition for building intuitive, well-documented, and highly maintainable APIs and shared platforms.
You have a track record of owning services with real uptime expectations. You design for observability from day one and aren't afraid of on-call responsibilities for the systems you build.
You excel at breaking down complex, open-ended problems into clear technical designs, moving from first principles to production-ready systems with both speed and rigor.
You treat the platform as your own. You care about the end-to-end lifecycle of your systems.
You have integrated or managed standard ML experiment tracking, artifact management, and model registries (e.g., Weights & Biases, MLflow, ClearML) or orchestrators (e.g., Ray, Flyte, Kubeflow).
You have designed and operated high-throughput data pipelines and resilient asynchronous workflows using durable execution engines (e.g., Temporal), streaming platforms (e.g., Kafka), or distributed compute frameworks (e.g., Spark, Flink).
You have navigated strict compliance frameworks (e.g., SOC2, FedRAMP) or built systems specifically for highly regulated, air-gapped, or on-premise environments.
Work alongside senior engineers from Tesla, DeepMind, Databricks, and other top engineering orgs.
Ship fast, learn constantly, and see your work protect production systems used by millions.
Earn competitive compensation and meaningful equity in a high-growth company.
Competitive salary plus equity
Daily lunches
Commuter benefits
401(k)
Medical, Dental, and Vision
Unlimited PTO
