Senior Azure AI Document Intelligence Engineer (OCR Experience) // Hybrid

Job Title: Senior Azure AI Document Intelligence Engineer (OCR Experience) (Hybrid 3 days' Work

from Office)

Location: Irving, TX

Duration: Long term Contract

Mode of Work:

I am also including the Job Description below:

Job Description:

Senior Azure AI Document Intelligence Engineer (OCR Experience)

We are seeking a Senior Azure AI Document Intelligence Engineer responsible for designing, training, and optimizing AI-powered contract and invoice OCR solutions using Azure AI Document Intelligence, Azure Databricks, Azure Machine Learning, MLflow, Azure AI Search, OpenAI/GenAI, Python, and SQL, driving 98-99%+ extraction accuracy across complex supply-chain and procurement documents through advanced machine learning, document classification, validation frameworks, and intelligent automation.

Roles and Responsibilities:

• 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, and totals Payment terms, renewal dates, obligations, and 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 Duplicate-document detection
• Required-field and cross-field consistency checks 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.

Experience: -10+ Years

Location: - Irving, TX (Hybrid 3 days' Work from Office)

Skills: -

Mandatory skills

• 4+ years of experience in machine learning, OCR, computer vision, NLP, or intelligent document processing. Hands-on 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 line items. Experience creating labelled datasets and maintaining data-quality standards. Familiarity with invoices, purchase orders, contracts, or supply-chain documents.
• Strong analytical, debugging, and technical-documentation skills. Preferred Qualifications Experience with Azure Machine Learning, MLflow, Azure AI Search, or Azure OpenAI. Experience with multilingual documents.
• Familiarity with contract clause extraction and legal-document processing. Knowledge of ERP or procurement systems such as SAP, Oracle, Dynamics 365, Coupa, or Ariba. Experience implementing active learning, model-drift monitoring, and human-in-the-loop workflows. Knowledge of data privacy and document-retention requirements.
• Success Measures 99% exact-match accuracy for approved critical fields. 98% exact-match accuracy across all agreed fields. Accuracy maintained across suppliers, formats, and document-quality categories.
• Measurable reduction in manual corrections and review time. Documented improvement process for fields that miss their thresholds. No production model deployed without passing the approved evaluation suite.

Skills

Azure (Bigdata Azure) Azure AI Document Intelligence, Azure Databricks, OpenAI, GenAI, Contract and Invoice OCR