What the Hell is an AI Engineer? | A Conversation with Amanda Richardson (CEO of CoderPad) & Jeff Queisser (Co-Founder of Box)
This week at Enrich, we brought together two seasoned technology leaders — Amanda Richardson, CEO of CoderPad, and Jeff Queisser, Co-Founder of Box — to unpack one of the buzziest job titles in tech today: the AI Engineer. The crux of this conversation: what does this role actually mean, and do companies really need it?
Amanda and Jeff spoke candidly about what they’re seeing inside fast-growing startups and public companies alike — from hype-driven hiring to the practical skills that actually matter.
If you’d been there, here’s what you’d still be thinking about:
“AI Engineer” isn’t a single job — it’s three different buckets.
Amanda was blunt: “Hot take — that is not a thing.” Instead, at CoderPad she sees three profiles hiding under the catch-all title:
Engineers building AI features into products (familiar with LLM APIs and applied tooling).
Rare, highly specialized researchers (PhDs or deep ML backgrounds, extremely costly and scarce).
AI literacy evangelists who help teams adopt tools and build cultural habits around usage.
Jeff agreed, noting some companies now stand up small “AI enablement” groups internally. These groups are less about novel tech, and more about ensuring engineers actually use the tools available.
Hype vs. reality: applied AI engineers as a “signal.”
Jeff shared a story of a company he’s working with who was trying to hire backend engineers for a chatbot project. The engineers in the recruiting pipeline were technically capable of building… but uninterested in the actual project. Only after posting the role as “Applied AI Engineer” did they get applicants excited to do the work. The lesson: sometimes the title is more about attraction than a discrete skill set.
Amanda added that excitement matters. “Latch onto the people who are drawn to it, because they’re the ones who will actually build stuff they’re excited about — and that’s what every great engineer should be doing.”
Adoption is cultural, not top-down.
Both speakers pushed back on the idea that CEOs can declare an “AI-first” strategy and expect change. The culture change is more challenging than the technical adoption. Jeff emphasized that “the CEO shaking a stick is not going to get people to change their daily workflows.” What he’s seeing work more effectively is peer-to-peer adoption, where one engineer shows another how they’ve tuned rules, prompts, or workflows to make AI valuable.
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