Applied AI Engineer, Generalist

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...

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 ca...

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.
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

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