AI Engineer
An AI Engineer builds and operates production systems with language models at their core. The role requires LLM application architecture and AI evaluation at Level 3, plus strong integration and debugging skills — it is an engineering role where the hardest problems are non-deterministic.
Also called: LLM engineer, GenAI engineer, applied AI engineer
What skills does a ai engineer need?
AI Engineering is where software engineering meets a dependency that is probabilistic, expensive, and occasionally confidently wrong. The distinguishing judgment is architectural: where the model sits, what it is trusted with, and what the fallback is. Strong candidates come from backend engineering, but the ones who succeed have added evaluation discipline that traditional engineering never required.
| Skill | Level | What that means | Status |
|---|---|---|---|
| LLM Application Architecture | L3 Independent | Makes justified trade-offs between model tiers, caching, and retrieval, and designs explicit fallback behaviour for model failure. | Required |
| AI Evaluation | L3 Independent | Designs evals that target real failure modes, chooses metrics that resist gaming, and knows the limits of what the eval measures. | Required |
| API & Systems Integration | L3 Independent | Designs for idempotency and partial failure, and makes state recoverable when the remote system misbehaves. | Required |
| Debugging & Diagnosis | L3 Independent | Diagnoses failures where the error is misleading, tests the cheapest hypothesis first, and verifies the root cause before fixing. | Required |
| Retrieval & RAG Systems | L2 Working | Tunes chunking and retrieval parameters against observed failures rather than by default settings. | Nice to have |
| Prompt Engineering | L2 Working | Uses structure deliberately — output formats, examples, explicit constraints — and can explain why a given prompt fails on a given input. | Nice to have |
No years-of-experience row, deliberately. Seniority is the level.
Which candidates does a CV screen miss for this role?
These job titles regularly belong to people who can do this work at the required level, and regularly fail a keyword screen for it.
Who currently scores highest
Live from the scoring engine — ranked on proof, with the CV title shown so you can see what a keyword filter would have done.
How do you assess a ai engineer?
Hiring a ai engineer near you
AI Engineer: questions people ask
- What is the difference between an AI Engineer and an ML Engineer?
- ML Engineers train and serve models. AI Engineers build products on top of models someone else trained. Different skill sets — this role needs architecture and evaluation, not gradient descent.
- How much AI experience do employers require?
- In skill terms, Level 3 in LLM application architecture and evaluation. In time terms, we do not ask, because a backend engineer six months into shipping AI features often exceeds someone with two years of adjacent exposure.
- Can a backend engineer move into AI engineering?
- It is the most common path we see. The transferable part is large; the gap is usually evaluation. Prove AI Evaluation at Level 3 and most AI Engineer specs open up.