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Azure AI Document Intelligence Engineer

URSI Technologies Inc.Irving, TX🇺🇸United StatesPosted 11 Aug 2026

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

Job Title: Senior Azure AI Document Intelligence Engineer (OCR)

Location: Irving, TX – Hybrid (3 days onsite)
Duration: Contract
Experience: 10+ Years
Education: BE/ME/BTech/MTech/BSc/MSc or equivalent

Job Overview

We are seeking a Senior Azure AI Document Intelligence Engineer with strong hands-on experience in OCR, Machine Learning, Computer Vision, NLP, and Intelligent Document Processing.

The ideal candidate will design, train, optimize, and deploy AI-powered contract and invoice document-processing solutions using Azure AI Document Intelligence, Azure Databricks, Azure Machine Learning, MLflow, Azure AI Search, Azure OpenAI/GenAI, Python, and SQL.

The role will focus on achieving 98–99%+ extraction accuracy across complex supply-chain, procurement, invoice, and contract documents.

Key Responsibilities

  • Analyze invoice and contract variations across suppliers, countries, languages, formats, and scan-quality levels.

  • Define document taxonomy and extraction schemas for invoices, contracts, purchase orders, supplier/customer information, dates, currencies, taxes, totals, payment terms, clauses, and line items.

  • Work with Azure AI Document Intelligence prebuilt, layout, custom neural, custom template, classification, and composed models.

  • Build, train, evaluate, and optimize custom document classification and extraction models.

  • Prepare, label, clean, balance, version, and maintain high-quality training/evaluation datasets.

  • Implement document preprocessing for rotation, skew, noise, resolution, page separation, and poor scan quality.

  • Develop confidence-scoring and validation frameworks using OCR and field-level confidence signals.

  • Implement validation rules for subtotal/tax/total reconciliation, currency/date validation, PO and supplier matching, duplicate detection, and cross-field consistency.

  • Establish confidence thresholds and human-in-the-loop review processes for uncertain extractions.

  • Perform detailed error analysis by document type, supplier, field, language, and document quality.

  • Build automated evaluation pipelines measuring accuracy, precision, recall, F1 score, false positives, and false negatives.

  • Monitor model performance and drift and retrain models as document formats and business requirements evolve.

  • Maintain documentation for model versions, training datasets, experiments, limitations, and production release decisions.

  • Collaborate with Supply Chain, Procurement, Accounts Payable, Legal, and Engineering teams.

Mandatory Skills

  • 4+ years of hands-on experience in Machine Learning, OCR, Computer Vision, NLP, or Intelligent Document Processing.

  • Strong experience with Azure AI Document Intelligence or a comparable enterprise document-processing platform.

  • Strong Python development skills.

  • Experience with REST APIs, JSON, Azure SDKs, and asynchronous processing.

  • Experience training and evaluating document classification and field-extraction models.

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

  • Experience extracting complex tables and variable-length invoice line items.

  • Experience creating and maintaining labeled datasets and data-quality standards.

  • Experience working with invoices, purchase orders, contracts, or supply-chain documents.

  • Strong analytical, debugging, problem-solving, and technical documentation skills.

Preferred Skills

  • Azure Machine Learning

  • MLflow

  • Azure Databricks

  • Azure AI Search

  • Azure OpenAI / GenAI

  • Multilingual document processing

  • Contract clause extraction and legal-document processing

  • ERP/procurement platforms such as SAP, Oracle, Dynamics 365, Coupa, or Ariba

  • Active learning and model-drift monitoring

  • Human-in-the-loop workflows

  • Data privacy and document-retention requirements

  • SQL

Success Measures

  • Achieve ≥99% exact-match accuracy for approved critical fields.

  • Achieve ≥98% exact-match accuracy across agreed extraction fields.

  • Maintain accuracy across different suppliers, formats, languages, and document-quality levels.

  • Reduce manual corrections and document-review time.

  • Establish a measurable continuous-improvement process for fields below accuracy thresholds.

  • Ensure no production model is deployed without successfully passing the approved evaluation suite.

Core Technology Stack

Azure | Azure AI Document Intelligence | Azure Databricks | Azure Machine Learning | MLflow | Azure AI Search | Azure OpenAI | GenAI | Python | SQL | OCR | Machine Learning | Computer Vision | NLP | Intelligent Document Processing

If this opportunity aligns with your experience, please share your updated resume, current location, work authorization, availability, and expected rate.

Skills

Oracle
SQL
MLflow
Machine Learning
NLP
Accounts Payable
Azure
ERP
Computer Vision
Data Privacy
Databricks
Procurement
Python
REST
Reconciliation
SAP

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