MincaAI builds AI-powered workflow automation software for the insurance industry. We design intelligent agents that automate complex, repetitive operational processes — from document intake and data extraction to smart matching and decision support — so that teams can focus on high-value work instead of manual tasks.
We are looking for an AI/LLM Engineer to own the LLM layer across our platform: what it extracts, what it classifies, how we know it works, what it costs, and how it improves every week without a retrain.

? The problem
Insurance runs on documents that were never designed to be read by a machine. A broker sends a fleet spreadsheet with headers in three conventions. A carrier returns a quotation as a PDF. An endorsement arrives as an email where the number that matters sits inside a sentence.
All of it has to become structured, typed, validated data — with a confidence score on each field, because a field that is silently wrong costs more than a field that is missing.
We already run this in production:



our vehicle codifier resolves free-text descriptions against the Mexican AMIS catalog at ~84% Top-1, with a three-way decision and a review queue that feeds corrections back in. Extraction and classification sit around it, and that is where most of the remaining error budget lives.

? What you'll do
Own extraction end-to-end — spreadsheets, PDFs, emails, OCR output into typed records with per-field confidence. Schema, prompts, validation, repair.
Build classification components — document type, vehicle type, coverage, use type. Measured models with owned metrics, not prompt strings someone tweaks.
Own the evaluation harness — golden sets, regression suites, CI gates, drift tooling between prompt and model versions.
Instrument and optimise the AI layer — quality, latency, degradation, cost per call. Model routing, caching, structured outputs, provider fallback.
Close the feedback loop — reviewer corrections become few-shot banks, alias dictionaries, routin

📌 AI/LLM engineer (Argentina)
🏢 MincaAI
📍 Argentina