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# AI Engineer Ads Demand Eight Years of Experience for a Three-Year-Old Job. Here’s What the Impossible Number Actually Filters For.

**[Noor Mohammad](https://daily.dev/sources/ew9hy5zthevyyefagop4g)** · [@noormohammad](https://daily.dev/noormohammad) · 1 min read · 0 upvotes · 1 comments

## Summary

Job ads for AI engineer roles routinely demand 5-8 years of experience despite the role only crystallizing around 2023, echoing the famous case where FastAPI's creator couldn't meet a job ad's 4+ years FastAPI requirement in 2020. Since impossible experience numbers can't be a genuine requirement, the piece argues the number functions as a filter for something else, while AI engineering is simultaneously reported as the fastest-growing job for young workers, meaning hiring happens despite the unrealistic ads.

## Content

July 2020: Sebastián Ramírez finds a job ad requiring 4+ years of FastAPI experience. His reply became one of the most-shared engineering posts ever — he couldn't apply, having only 1.5 years, since he created it.

2026: AI engineer ads routinely demand 5–8 years. The role (LLM apps, retrieval, evals, agents) crystallised around 2023. Eight years of it isn't scarce — it's **nonexistent**.

Meanwhile the same market reports AI engineering as the fastest-growing job _for young workers_. Ads demand impossible seniority; hiring happens anyway.

So the number isn't a requirement, it's a password. What it actually filters for, and the evidence that beats it. 🔗
[https://medium.com/@thebuildersplaybook/ai-engineer-ads-demand-eight-years-of-experience-for-a-three-year-old-job-fa07c35a15c8?sharedUserId=thebuildersplaybook](https://medium.com/@thebuildersplaybook/ai-engineer-ads-demand-eight-years-of-experience-for-a-three-year-old-job-fa07c35a15c8?sharedUserId=thebuildersplaybook)

## Community discussion

Top comments from developers on daily.dev.

**@noormohammad** · 0 upvotes

> The FastAPI story is the perfect precedent because it's arithmetically undeniable — the author of the framework was excluded by the ad for it.
>
> Practical question: for those who've been hired into AI engineering roles recently, what actually got you through — shipped projects, evals/RAG work you could demo, or just applying anyway despite the years line? My read is the gap between stated and actual requirements has never been wider, but I'd like real data points.

---

Tags: [#llm](https://daily.dev/tags/llm), [#ai-engineering](https://daily.dev/tags/ai-engineering)

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