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Description Role Summary This role owns the document ingestion and extraction pipeline: turning scanned forms, PDFs, and other unstructured records into clean, structured, validated data ready for indexing, search, and downstream workflows. The person in this role builds the confidence-scoring and human-in-the-loop review mechanisms that keep extracted data trustworthy at scale. Key Responsibilities Build and maintain document ingestion pipelines using Azure AI Document Intelligence (Form Recognizer). Implement OCR, document classification, and metadata/field extraction for scanned PDFs and mixed-format records. Design confidence-scoring logic and exception/review queues for low-confidence extractions. Build batch processing pipelines using Azure Functions, Logic Apps, or Data Factory. Model and maintain extraction and metadata data structures in SQL. Implement data quality checks, duplicate detection, and validation rules across the pipeline. Partner with the Search Engineer to ensure extracted data feeds cleanly into indexing. Requirements Required Qualifications Production experience with Azure AI Document Intelligence / Form Recognizer. Strong OCR and document classification experience, including scanned/handwritten forms. Experience with confidence scoring and human-in-the-loop validation design. Proficiency in Python and SQL for data processing and pipeline development. Experience with Azure Functions, Logic Apps, or Data Factory (or equivalent batch/serverless tooling). Demonstrated experience handling data quality issues: duplicate detection, exception handling, reconciliation. Preferred Qualifications Experience with LLM-assisted structured extraction (JSON schema outputs, prompt-based field extraction). Healthcare, insurance, legal, or government document-processing background. Familiarity with HIPAA-, FedRAMP-, or similarly regulated data-handling practices.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.