layiq
/la·yiq/adjective
worthy; deserving; fitting; suitable.
A role, opportunity, or path that merits attention, time, and pursuit.
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Job opportunity
Applied AI Engineer, Generalist
Sable
San Francisco, California, United States
Source: Sable careers · View original posting
Employer job description
From Sable's posting. “We” and “our” refer to the employer.
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