How to Hire AI Developers Who Ship to Production
Building an AI demo takes an afternoon. Shipping a reliable AI feature takes engineering. Here is how to hire AI developers who can do the second part.
To hire AI developers who ship to production, look beyond prompt demos. Test software engineering fundamentals, retrieval-augmented generation (RAG), evaluation methods, cost and latency control, and data security. The best AI developers can show a deployed feature, how they measured its quality and what they did when it failed.
Demo skills vs production skills
| Demo skills | Production skills |
|---|---|
| Calling an LLM API | Handling timeouts, retries and rate limits |
| Clever prompts | Versioned prompts with automated evaluation |
| Small document sets | Scalable retrieval with chunking and re-ranking |
| Ignoring cost | Caching, model routing and token budgets |
| Happy path | Guardrails, PII redaction and fallbacks |
Core skills to test
- Python or TypeScript engineering with tests and clean APIs.
- RAG pipelines — chunking strategies, embeddings, vector databases, hybrid search.
- Evaluation — golden datasets, LLM-as-judge with care, human review.
- Observability — tracing with tools like Langfuse or LangSmith.
- Security and privacy — data masking, zero-retention settings, access control.
Interview questions
- How do you know your AI feature is getting better, not worse?
- What do you do when retrieval returns the wrong documents?
- How would you cut our token spend in half?
- How do you handle prompt injection?
A practical assessment
Provide a handful of documents and ask for a small question-answering service with citations, plus a short evaluation script with ten test questions. Discuss results and failure cases.
Pick the right specialist
General AI developers suit most product features. For content generation and fine-tuning, consider generative AI developers; for multi-step automation, AI agent developers.
