Intelligent Document Processing / OCR Engineer - Part Time

Designs and implements the intelligent document-processing capabilities required to convert electronic records into reliable, structured, and traceable information. The Intelligent Document Processing / OCR Engineer assesses the document corpus and document quality; applies OCR, image preprocessing, and layout analysis where required; supports duplicate detection; develops document-classification and structured field-extraction methods; and establishes confidence scores, validation rules, exception-handling procedures, and human-review thresholds.

The Engineer configures and tunes OCR models, preprocessing techniques, classification methods, extraction schemas, confidence thresholds, and validation logic based on testing results and representative document samples. The position establishes measurable evaluation methods for OCR quality, classification accuracy, field-extraction accuracy, exception rates, and human-review requirements. Processing configurations, quality results, known limitations, and operating procedures are documented to support explainability, repeatability, troubleshooting, and knowledge transfer.

The Engineer works within the overall architecture established by the Microsoft Cloud Solution Architect / Technical Lead and coordinates closely with platform, data, security, quality assurance, AI search, and Government subject-matter personnel. The position also supports automated processing of newly added or modified documents so that files can be assessed, preprocessed, classified, extracted, validated, and routed for human review or downstream indexing with minimal manual intervention. The greatest level of effort is expected during corpus assessment, OCR and preprocessing configuration, classification and extraction development, validation-rule definition, quality testing, and document-processing automation.

Key Responsibilities

• Assess document collections, formats, and quality to determine appropriate OCR and processing approaches.
• Configure and tune OCR, image preprocessing, and layout-analysis capabilities for scanned, image-based, degraded, and digitally generated documents.
• Develop document-classification methods, taxonomies, and associated processing rules.
• Develop structured field-extraction schemas, metadata mappings, validation rules, and extraction logic.
• Establish confidence scores, acceptance thresholds, exception criteria, and human-review requirements.
• Design and support exception-handling and human-validation workflows for incomplete, ambiguous, or low-confidence processing results.
• Support duplicate-detection and document-quality controls within the processing workflow.
• Develop or support automated processing workflows for newly added or modified documents, including ingestion, classification, extraction, validation, and exception routing.
• Define, measure, and tune OCR quality, classification accuracy, and field-extraction accuracy using representative document samples.
• Document processing configurations, quality results, known limitations, validation procedures, and operating instructions to support testing, deployment, and knowledge transfer.