AI Engineer

Що робити

• You own the analysis engine. The attributes and scoring rules that decide whether a model can understand a business are the core of the product, and keeping them at their sharpest is on you. When model behaviour moves, you’re the one who spots it, works out what it means for our rules, and either ships the change or makes the case for it
• The evaluation framework. Ground-truth sets, metrics, and regression detection that survives the fact that the thing you’re measuring answers differently every time you run it. Most of the rest of this list is blocked without it
• Retrieval. Getting text out of real websites, deciding how to chunk it, picking an embedding model, and keeping a path from every claim we make back to the page it came from.
• The agentic architecture. One agent, several, or a plain tool-use pipeline. You’d work out which fits and say why in terms of cost and latency rather than preference. We haven’t settled this yet
• Model selection and cost per run. Benchmarking frontier models against open-weight ones, then routing so we only pay for the expensive option where it changes the answer.