Headlines love to say there are not enough AI engineers to go around. If you have tried to hire one locally, you have probably felt it: long searches, high salary expectations and candidates who disappear to bigger companies. But "shortage" hides an important detail — the shortage is not evenly spread.
Where the shortage is real
There genuinely are few people who research new model architectures, train large models from scratch or lead AI teams at scale. Big tech competes hard for them. If your project needs that kind of research work, expect a long and expensive search.
Where it is not
Most businesses do not need researchers. They need engineers who can:
- Connect existing AI models (via APIs) to their data and workflows
- Build retrieval-augmented (RAG) chatbots over company documents
- Automate repetitive tasks such as data entry, email triage or reporting
- Add AI features — summaries, classification, recommendations — to existing apps
These are applied engineering skills. Strong Python, API and web developers learn them quickly, and the global pool of people doing this work is large and growing — including in India.
Why it feels like a shortage
- Job descriptions ask for everything. "PhD, 10 years of LLM experience, full-stack, DevOps" describes nobody.
- Searches stay local. Limiting yourself to one city shrinks the pool dramatically.
- The role is unclear. Without a defined problem, it is hard to judge any candidate.
What to do instead
- Define the business problem first. "Reduce support response time by answering common questions automatically" is hireable. "Do AI" is not.
- Hire for the work, not the title. An experienced Python or full-stack developer with API integration skills can deliver most applied AI projects.
- Look beyond your city. Remote and offshore developers widen your options and reduce cost.
- Start with a small, measurable pilot before committing to a large team.
The AI talent shortage is mostly a research-talent shortage. For applied business AI, the talent exists — you just need to scope the role clearly and look in the right places.
Conclusion
If your project is about using AI rather than inventing it, you are not competing for the rarest people in tech. Clear scoping, a realistic job description and a wider search will get you building far sooner than you might expect.
Planning an AI or automation project? Hire a Python developer or talk to us about your idea.