Azure AI Document Intelligence Engineer

Tasks

• Analyse invoice and contract variations across suppliers, countries, languages, formats, and scan-quality levels.
• Define the document taxonomy and extraction schema for invoice headers, contract metadata, purchase-order references, supplier and customer information, dates, currencies, taxes, discounts, totals, payment terms, renewal dates, obligations, termination clauses, tables, and invoice line items.
• Evaluate Azure AI Document Intelligence prebuilt invoice, layout, custom neural, custom template, classification, and composed-model capabilities.
• Build and train custom document classifiers and extraction models.
• Prepare, label, clean, balance, and version training and evaluation datasets.
• Implement document preprocessing for rotation, skew, noise, resolution, page separation, and scan-quality issues.
• Develop confidence-scoring and validation strategies using field-level and OCR-level confidence signals.
• Implement deterministic validation rules, including subtotal, tax, and total reconciliation; currency and date validation; purchase-order and supplier matching; and duplicate-document detection.
• Establish confidence thresholds and human-review rules for uncertain extractions.
• Perform error analysis by document type, supplier, field, language, and scan quality.
• Create automated evaluation pipelines reporting exact-match accuracy, precision, recall, F1 score, false-positive rates, and false-negative rates.
• Monitor model drift and retrain models when document formats or business requirements change.
• Document model versions, training data, experiments, limitations, and release decisions.
• Collaborate with supply-chain, procurement, accounts-payable, legal, and engineering teams.

Schedule

• Long-Term Contract - W2/C2C

How to apply

• DM

Location

• Irving, TX/ Eden Prairie, MN / Chicago, IL