Senior Azure AI Document Intelligence Engineer

Hi,

We are hiring !!

!
Senior Azure AI Document Intelligence Engine

er
Irving,

TX
We are seeking a Senior Azure AI Document Intelligence Engineer to design, train, evaluate, and continuously improve the document-processing models used for supply-chain contracts and invoi

ces.This engineer will own extraction quality and be directly accountable for achieving the project’s 98–99% accuracy objecti

ves.Key Responsibili

tiesAnalyze invoice and contract variations across suppliers, countries, languages, formats, and scan-quality lev

els.Define the document taxonomy and extraction schema

for:Invoice hea

dersContract meta

dataPurchase-order refere

ncesSupplier and customer informa

tionDates, currencies, taxes, discounts, and to

talsPayment terms, renewal dates, obligations, and termination cla

usesTables and invoice line i

temsEvaluate Azure AI Document Intelligence prebuilt invoice, layout, custom neural, custom template, classification, and composed-model capabilit

ies.Build and train custom document classifiers and extraction mod

els.Prepare, label, clean, balance, and version training and evaluation datas

ets.Implement document preprocessing for rotation, skew, noise, resolution, page separation, and scan-quality iss

ues.Develop confidence-scoring and validation strategies using field-level and OCR-level confidence sign

als.Implement deterministic validation rules, includ

ing:Subtotal, tax, and total reconcilia

tionCurrency and date valida

tionPurchase-order and supplier matc

hingDuplicate-document detec

tionRequired-field and cross-field consistency ch

ecksEstablish confidence thresholds and human-review rules for uncertain extracti

ons.Perform error analysis by document type, supplier, field, language, and scan qual

ity.Create automated evaluation pipelines reporting exact-match accuracy, precision, recall, F1 score, false-positive rates, and false-negative ra

tes.Monitor model drift and retrain models when document formats or business requirements cha

nge.Document model versions, training data, experiments, limitations, and release decisi

ons.Collaborate with supply-chain, procurement, accounts-payable, legal, and engineering te

ams.Required Qualificat

ionsBachelor’s or master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related discipl

ine.4+ years of experience in machine learning, OCR, computer vision, NLP, or intelligent document process

ing.Hands-on experience with Azure AI Document Intelligence or a comparable enterprise document-processing platf

orm.Strong Python development ski

lls.Experience with REST APIs, JSON, Azure SDKs, and asynchronous process

ing.Experience training and evaluating document classification and field-extraction mod

els.Strong understanding of accuracy, precision, recall, F1 score, confidence calibration, and test-set des

ign.Experience extracting complex tables and variable-length line it

ems.Experience creating labeled datasets and maintaining data-quality standa

rds.Familiarity with invoices, purchase orders, contracts, or supply-chain docume

nts.Strong analytical, debugging, and technical-documentation ski

lls.Preferred Qualificat

ionsExperience with Azure Machine Learning, MLflow, Azure AI Search, or Azure Ope

nAI.Experience with multilingual docume

nts.Familiarity with contract clause extraction and legal-document process

ing.Knowledge of ERP or procurement systems such as SAP, Oracle, Dynamics 365, Coupa, or Ar

iba.Experience implementing active learning, model-drift monitoring, and human-in-the-loop workfl

ows.Knowledge of data privacy and document-retention requireme

nts.Success Meas

ures≥99% exact-match accuracy for approved critical fie

lds.≥98% exact-match accuracy across all agreed fie

lds.Accuracy maintained across suppliers, formats, and document-quality categor

ies.Measurable reduction in manual corrections and review t

ime.Documented improvement process for fields that miss their thresho

lds.No production model deployed without passing the approved evaluation su