Posting record
Open 12+ days
- Attention's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Attention, so its true age is longer.
Last checked Nov 2, 2026.
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Upload your resumeWhat the posting discloses
- Pay
- $180k a year USD
- AI screening
- Uses AI to screen applicants
AI Runtime & Agent Orchestration: context management, tool use, VLMs, model selection, output quality in production. (quoted from the posting)
Not stated: Real vacancy.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Skills mentioned
About the role
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.
The Team
We’re a small team of builders/researchers. We’ve worked at companies like Citadel, Jane Street, and Optiver, published papers at the top AI conferences, won IOI gold medals, and more.
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.
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