Posting record
Open 12+ days
- Sable'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 Sable, so its true age is longer.
Last checked Nov 2, 2026.
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Upload your resumeWhat the posting discloses
Not stated: Pay, real vacancy, AI screening.
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.
Some employers add pay only on their own site. Check the original posting before you rule it out.
Skills mentioned
About the role
About Sable
Sable built Aidan, the first AI employee who can lead customer calls using realtime voice, vision, and browser use. Aidan runs a live, two-way conversation inside a real product environment, clicking through the product like a human, watching the user's screen, and adapting the journey on the fly. Every conversation feeds a self-improving context graph we call the Brain, so Aidan gets smarter with each call.
The role
You build Aidan himself. You empower Aidan to orchestrate his abilities across four modalities in realtime: voice (two-way, multilingual conversation), hands (live browser use inside real products), eyes (proactive vision on the user's screen), the Brain (a self-improving context graph), and the verifiers (how we can keep evaluating Aidan's performance in real scenarios). Making that feel human is one of the hardest engineering problems in AI, and our engineering team's unique ability to solve it is what makes Sable special. You are an individual contributor first. You can also take a project that spans several engineers, break it into pieces, keep it on track, and land it. That is coordination, not management. We are hiring someone who ships fast and makes the people around them ship.
What you'll do
- Own large changes to the agent runtime end to end: design, implementation, evaluation, rollout
- Run multi-person projects: write the plan, split the work, review the pieces, keep the whole thing coherent
- Raise the bar on how the team works: review quality, test discipline, how we verify a change before it ships
Who you are
- Two or more years building software, with a stretch owning a system that mattered in production
- Strong generalist: backend and systems by default, comfortable in frontend, infra, or ML code when the problem lives there
- You have coordinated projects across several people and enjoyed it
- Comfortable in a small team where you own problems end to end and communicate fluidly
- Bonus: Someone with deep experience in at least one of: realtime systems (voice/streaming/media), LLM agents and orchestration, browser/computer use, and applied ML such as multimodal evals
- Bonus: previous experience at a leading AI company or institution
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