About Attention Engineering
The gap between how top engineers around the world use AI systems today - elaborate coding agent configs, massive context files, and engineered workflows - and how everyone else uses it is only growing.
We think the company that bridges the gap to create a sovereign product that understands and multiplies the rest of the worlds output will be one of the most important companies built in this decade.
In the words of William Gibson, "The future is already here — it's just not evenly distributed."
The Team
Our team is small, talent dense, and well funded by great investors. We've worked at Jane Street/Citadel/HRT, won medals at the International Olympiads, and have published in top ML conferences.
If your background doesn’t fit cleanly into one of the buckets above, that’s fine. We care about ownership, experience building, and slope, rather than your pedigree.
The Role
We are hiring one title across multiple strengths. You will own large, critical parts of the system. We hire across a few different spikes, but the bar is exceptional individuals. You’re spike may be:
AI Runtime & Agent Orchestration: context management, tool use, VLMs, model selection, output quality in production.
Search, Retrieval, Vector Systems & Data Infrastructure: Embedding pipelines, ranking and retrieval architecture, and data infrastructure underneath.
Evals, Applied ML & Model Quality.
Backend Systems & Workflow Architecture: PostgreSQL, Redis, Pub/Sub, FastAPI
Infrastructure, Cloud Platform & Reliability: GCP, Terraform, Docker, Cloud Run.
You will work directly on the product, platform, and infrastructure with no layers between you and the decisions that matter.