AI Platform Backend. Engineer, Capabilities

Brain Co.•San Francisco, CA

About The Position

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.

Requirements

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++).
Deep grasp of consistency, availability, distributed failure modes, and idempotency.
Strong intuition for building intuitive, well-documented, and highly maintainable APIs and shared platforms.
Track record of owning services with real uptime expectations. Design for observability from day one and aren't afraid of on-call responsibilities for the systems you build.
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.
Care about the end-to-end lifecycle of your systems.

Nice To Haves

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).
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).
Navigated strict compliance frameworks (e.g., SOC2, FedRAMP) or built systems specifically for highly regulated, air-gapped, or on-premise environments.

Responsibilities

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.