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Azure Ai Document Intelligence Jobs (NOW HIRING)

Tech Mirrors

WI · On-site

$150 - $230/hr

Define AI strategy using Azure OpenAI Service, Azure AI Search, Azure AI Document Intelligence, Azure AI Foundry, Microsoft Foundry and Azure Machine Learning. * Ensure compliance with banking ...

Expert Technology Services

AI Architect

Houston, TX · On-site

$60.75 - $79/hr

... Azure AI Search, vector databases, Semantic Kernel, and RAG frameworks. - Led development of enterprise copilots, intelligent assistants, document intelligence solutions, and knowledge management ...

TrnDigital

Be Seen First

AI Architect

Newton, MA · Remote

$180K - $220K/yr

Lead technical design using Microsoft Foundry, Azure AI Search, Azure Document Intelligence, LangChain, LangGraph, and LangSmith. * Collaborate with clients to understand requirements, translate them ...

Coforge

DDCS Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

Create OCR-based document processing pipelines for scanned and handwritten PDFs using Azure AI Document Intelligence or similar tools. * Build and manage data solutions on Azure Fabric, including ...

Inficare Technologies

AI Engineer - Generative AI

... document intelligence platforms, multimodal AI applications, and scalable AI APIs using Azure OpenAI and Python. Key Responsibilities * Design, develop, and deploy enterprise Generative AI ...

Resource Consultings Services Inc

AI Architect IV

Houston, TX · On-site

$60.75 - $79/hr

Develop Generative AI solutions including enterprise copilots, intelligent assistants, document intelligence, and knowledge management systems. * Leverage Azure AI Search, vector databases, Semantic ...

Noblesoft Technologies

GEN AI Architect

Charlotte, NC · On-site

Architect end-to-end AI model workflows, utilizing Azure AI, and Google AI tools. Focus will be on applications involving complex document intelligence, multi-modal data analysis, and advanced image ...

Noblesoft Technologies

Gen AI Architect

Jersey City, NJ · On-site

Architect end-to-end AI model workflows, utilizing Azure AI, and Google AI tools. Focus will be on applications involving complex document intelligence, multi-modal data analysis, and advanced image ...

nFolks Data Solutions

AI Architect-Houston, TX

Houston, TX · On-site

$60.75 - $79/hr

Develop Generative AI solutions including enterprise copilots, intelligent assistants, document intelligence, and knowledge management systems. * Leverage Azure AI Search, vector databases, Semantic ...

Bounteous

Azure AI Foundry Architect

Scottsdale, AZ · On-site

$64 - $83.25/hr

Exceptional documentation and communication skills. * Ability to influence cross-functional teams ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Purple Drive

Senior AI Full Stack Developer

Boston, MA · On-site

... AI, Azure AI services, and modern data platforms. Key Responsibilities * Build AI-powered applications and agentic workflows. * Develop RAG-based knowledge, search, and document intelligence ...

Bounteous

Azure AI Foundry Architect

Scottsdale, AZ · Remote

$64 - $83.25/hr

Exceptional documentation and communication skills. * Ability to influence cross-functional teams ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Bounteous

Azure AI Foundry Architect

Scottsdale, AZ · Remote

$64 - $83.25/hr

Exceptional documentation and communication skills. * Ability to influence cross-functional teams ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

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All JobsAzure Ai Document Intelligence Jobs

Azure Ai Document Intelligence information

What is Azure AI Document Intelligence?

Azure AI Document Intelligence is a cloud-based service provided by Microsoft Azure that uses artificial intelligence to extract, analyze, and process information from documents such as invoices, receipts, forms, and more. It helps automate data extraction by recognizing key fields and values, turning unstructured data into structured, usable information. This service is commonly used to streamline document-heavy workflows, reduce manual data entry, and improve operational efficiency for businesses.

What are some common challenges faced by professionals working with Azure AI Document Intelligence, and how can they be addressed?

Professionals working with Azure AI Document Intelligence often encounter challenges such as handling documents with complex layouts, ensuring high accuracy in data extraction, and integrating the service into existing workflows. Overcoming these challenges typically involves leveraging pre-trained models, customizing training with domain-specific data, and collaborating closely with developers and business analysts to fine-tune extraction processes. Regularly testing the models and staying updated with Azure’s latest features can also help improve outcomes and streamline document processing within teams.

What are the key skills and qualifications needed to thrive as an Azure AI Document Intelligence Specialist, and why are they important?

To excel as an Azure AI Document Intelligence Specialist, you need a solid understanding of cloud computing, machine learning, and document processing, typically supported by a degree in computer science or a related field. Familiarity with Microsoft Azure services, especially AI Document Intelligence (formerly Form Recognizer), as well as experience with APIs, Python, and data integration tools is crucial. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret business needs and deliver tailored AI solutions. These competencies ensure accurate extraction and processing of information from documents, driving automation and efficiency in enterprise workflows.

What is the difference between Azure Ai Document Intelligence vs Data Scientist?

AspectAzure Ai Document IntelligenceData Scientist
Primary FocusAutomating document processing and extracting insights from unstructured data using AIAnalyzing data to develop models, insights, and predictions for business decisions
Required SkillsAI/ML, OCR, NLP, cloud services, data preprocessingStatistics, programming (Python/R), machine learning, data analysis
Work EnvironmentCloud platforms, AI tools, enterprise document workflowsData analysis environments, research labs, business analytics
CertificationsAzure certifications, AI/ML certificationsData Science certifications, Python/R certifications

Azure Ai Document Intelligence focuses on automating document processing using AI technologies, while Data Scientists analyze data to build predictive models. Both roles require AI and data analysis skills but serve different purposes within the data ecosystem.

What cities are hiring for Azure Ai Document Intelligence jobs?

Cities with the most Azure Ai Document Intelligence job openings:

What states have the most Azure Ai Document Intelligence jobs?

States with the most job openings for Azure Ai Document Intelligence jobs include:

What job categories do people searching Azure Ai Document Intelligence jobs look for?

The top searched job categories for Azure Ai Document Intelligence jobs are:

Azure Ai Document Intelligence jobs near you
Infographic showing various Azure Ai Document Intelligence job openings in the United States as of August 2026, with employment types broken down into 2% As Needed, 79% Full Time, 13% Part Time, 5% Contract, and 1% Nights. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

Data Solutions Architect, Billings Montana (onsite)

Tech Mirrors

WI • On-site

$150 - $230/hr

Other

Posted 22 days ago

Job description

Role: Data Solutions Architect

Location: Billings Montana (onsite) or nearby states allowing the candidate to travel frequently.

Visa: any (except OPT)

Must-Have Skills:
  • Strong understanding of Banking & Financial Services data domains such as Customer 360, Risk, Compliance, Fraud, Treasury, Lending and Regulatory Reporting.
  • 12–16 years of overall IT experience
  • 12-15 + years of hands‑on experience designing Modern Data Platforms including:
    • Data Ingestion & Pipelines
    • Data Lakes / Lakehouse / Data Warehouses
    • Business Intelligence & Advanced Analytics
  • Strong experience with Microsoft Fabric components including:
    • Fabric OneLake
    • Fabric Pipelines
    • Fabric Notebooks
  • Hands‑on expertise with Azure Data Factory, Azure Databricks, dbt and other Azure data services
  • Proven experience in Banking & Financial Services analytics use case analysis, source system analysis and data quality assessment. Experience with Fiserv Core platforms is a big advantage
  • Experience working with large-scale enterprise data platforms, high-volume datasets and analytical models
  • Strong understanding of Data Management principles:
    • Data Governance
    • Data Cataloging & Metadata Management
    • Data Security & Privacy
    • Master Data Management (MDM)
  • Familiarity with Modern Data Platform principles:
    • DataOps & CI/CD
    • Performance Optimization
    • Reliability, Scalability and Security
  • Strong knowledge of data architecture styles and design patterns
  • Experience leading Discovery & Design workshops with Banking & Financial Services business and IT stakeholders
  • Proven Expertise in implementing AI solutions to customers
  • Experience collaborating with onshore and offshore delivery teams
  • Hands‑on experience with Agile delivery models and Azure DevOps
  • Excellent communication, presentation and stakeholder management skills
Key Responsibilities :
  • Define end-to-end architecture leveraging Microsoft Fabric, Azure Data Platform and Azure AI Services.
  • Lead solution design across Data Engineering, Data Science, BI and AI workloads.
  • Architect Fabric components including OneLake, Data Factory, Lakehouse, Warehouse, Real-Time Analytics and Power BI.
  • Define AI strategy using Azure OpenAI Service, Azure AI Search, Azure AI Document Intelligence, Azure AI Foundry, Microsoft Foundry and Azure Machine Learning.
  • Ensure compliance with banking regulations, security, governance and risk management requirements.
  • Drive stakeholder engagement and align technology solutions with business objectives.
  • Provide architecture governance and technical leadership throughout delivery
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