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October 9, 2023
Powerful foundation models are now available at our fingertips via APIs and open source. This once in a generation shift is fueling the rise of the AI Engineer.
We launched the AI Engineering Survey (direct link to survey - here) in September, and surveyed 841 folks in AI Engineering to bring better data and transparency to the AI Engineering space. This is our first time running the survey. Below you’ll find preliminary results, lessons and learnings. We are excited to update this and track how these trends evolve over time.
Want to chat more? Reach out to Barr Yaron at [email protected] or fill out this form to be included in future reports.
Who took this survey?
The 841 respondents range from founders of small startups to engineers at Fortune 500 companies. They have different titles and origins— the most popular roles being software engineer, AI Engineer, data engineer, data scientist, and ML engineer. While these roles require some overlapping “AI Engineer” skillsets, our prediction is that the share of folks with the official title “AI Engineer” will continue to increase over time.
Top 5 roles
Top 5 industries
| Software Engineer | 18% |
|---|---|
| AI Engineer | 18% |
| Data Engineer | 14% |
| Data Scientist | 14% |
| ML Engineer | 12% |
| Other | 23% |
| SaaS | 57% |
|---|---|
| Developer Tools | 9% |
| Professional Services | 5% |
| Finance | 4% |
| Real Estate | 4% |
| Other | 21% |
<aside> ⏳ Some experienced folks are only recently adding AI to their repertoire.
Of the folks surveyed with 10+ years of software experience, 38% have < 3 years of AI/ML experience, and 20% have < 1 year of AI/ML experience!
</aside>
Years of Experience
We expect more folks across the software stack to build with AI models, and the development of tooling to be highly linked to functional role (e.g. ML researchers in python, app developers in JS/TS).