What is an “AI Engineer”?
AI engineering is a new category of technical work. Its emergence is linked to the increasing availability of powerful new artificial intelligence tools: notably generative machine learning systems like large language models.
The term was suggested by swyx on the Latent Space podcast and we’ve written about it on our blog before.
Elicit predicted the rise of powerful ML systems even before GPT-1 was trained, and has the deepest experience of building trustworthy, capable, and transparent applications using these tools.
If you’re a software engineer who relishes the more difficult parts of backend code—like concurrency, fault-tolerance, and distributed systems—you could be a great AI engineer.
Why we’re hiring for this role
Since launching the newest version of Elicit last fall, response has been strong. We introduced Elicit Plus, our monthly subscription plan, and added thousands of paying users in a matter of months as well as hundreds of thousands of new sign-ups. This has been energizing for our team, but we want to ship more useful functionality to our users even faster.
We believe that building great AI-powered products requires excellence across multiple parts of the tech stack: from frontend UX to infrastructure. But one of the crux areas is certainly how we prompt, invoke, respond to, and manage the suite of different ML models required to make Elicit work. This is what an AI engineer will be responsible for at Elicit.
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Backend: Node and Python.
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Frontend: Next.js and TypeScript (we expect you to be 80+% focussed on backend work, however).
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We like static type checking in Python and TypeScript
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All infrastructure runs in Kubernetes across a couple of clouds
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We use GitHub for code reviews and CI