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Azure Ai Document Intelligence Jobs (NOW HIRING)

Hirekeyz Inc

AI/Full Stack Engineer

Irving, TX · Remote

Utilize Azure AI services, including Document Intelligence, Azure OpenAI, and AI Search, to build intelligent features. Implement and manage MongoDB databases for application data storage. Contribute ...

CGI Inc.

AI Software Developer

Plymouth Meeting, PA · On-site

Experience with Intelligent Document Processing (IDP) solutions such as Azure AI Document Intelligence. . Experience deploying AI solutions on cloud platforms including Azure, AWS, or Google Cloud.

Echo IT Solutions

AI/Full Stack Engineer

Irving, TX · On-site

... Document Intelligence, Azure OpenAI, and AI Search, to build intelligent features. • Implement and manage MongoDB databases for application data storage. • Contribute to the development of end-to ...

Spark Tek Inc

AI/Full Stack Engineer

Irving, TX · On-site

... Document Intelligence, Azure OpenAI, and AI Search, to build intelligent features. • Implement and manage MongoDB databases for application data storage. • Contribute to the development of end-to ...

Perficient

Azure AI Data Architect

Saint Louis, MO · On-site

$59.50 - $77.50/hr

... documentation. You will challenge your leading edge solutions, consultative and business skills ... Our practice groups include Artificial Intelligence, Analytics, Content Management, Data Governance ...

Novia Infotech

NEED AI FULL STACK DEVELOPER

Boston, MA · On-site

Build RAG-based knowledge, search, document intelligence, and enterprise information solutions ... Azure AI Foundry and Azure OpenAI * RAG, Prompt Engineering, and Agentic AI frameworks such as ...

Perficient, Inc.

Azure AI Data Architect

Saint Louis, MO · On-site

$59.50 - $77.50/hr

... documentation. You will challenge your leading edge solutions, consultative and business skills ... Our practice groups include Artificial Intelligence, Analytics, Content Management, Data Governance ...

Bounteous

$140 - $190/hr

Job Title: Azure AI Foundry Architect Location: Remote (Onshore Preferred - 5 days onsite ... Exceptional documentation and communication skills. * Ability to influence cross-functional teams ...

GRP SCAN Group

Principal AI Architect

Long Beach, NY · On-site

$147.90 - $254.80/hr

Automate ingestion and evaluation processes for Document Intelligence, AI Search, and other Azure AI Services. Integrate monitoring, audit, and feedback loops to ensure operational transparency and ...

Bounteous

Azure AI Foundry Architect

Scottsdale, AZ · On-site

$140 - $190/hr

Job Title: Azure AI Foundry Architect Location: Remote (Onshore Preferred - 5 days onsite ... Exceptional documentation and communication skills. * Ability to influence cross-functional teams ...

Virtusa Corporation

AI Solutions Architect

Piscataway, NJ · On-site

$64.25 - $84.50/hr

... Azure document intelligence • Multi-threading in Python: nice to have o AsyncIO o Non blocking programming. • Lead end-to-end solutioning of AI agents and agentic workflows, including design ...

Lorven Technologies

Technical Architect - Data Platform

$65.25 - $84/hr

Strong experience with Microsoft Fabric (OneLake, Data Factory, Lakehouses, Delta Lake), Azure Document Intelligence, Microsoft Purview, Okta SSO, Python, SQL, Azure AI Services, Azure DevOps, Git ...

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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.

AI/Full Stack Engineer

Hirekeyz Inc

Irving, TX • Remote

Contractor

Re-posted 27 days ago

Job description

Role: AI/Full Stack Engineer

Location: Irving, TX (Remote)
 
Job Type: Contract
 
 
Job Description:
 
We are rapidly expanding our team and seeking highly skilled and experienced AI/Full Stack Engineers to contribute to the development and deployment of cutting-edge AI-powered applications. You will play a key role in building robust backend systems and integrating Large Language Models to create innovative solutions. This is a fast-paced environment requiring individuals who can hit the ground running and have a proven track record of delivering production-ready applications.
 

Required Skills -    

Python. backend development and AI integration. Language Models, with a primary focus on OpenAI.

Job Duties -    Responsibilities:

Design, develop, and deploy backend infrastructure and APIs to support AI-driven applications.
Integrate and work extensively with Large Language Models (primarily OpenAI).
Develop and refine prompts to optimize the performance and accuracy of LLMs.
Utilize Azure AI services, including Document Intelligence, Azure OpenAI, and AI Search, to build intelligent features.
Implement and manage MongoDB databases for application data storage.
Contribute to the development of end-to-end prototype applications with a focus on backend functionality and automated testing
Collaborate with cross-functional teams to understand requirements and translate them into technical solutions.
Ensure the scalability, reliability, and performance of deployed AI applications.
Apply GenAI concepts and techniques to solve real-world problems.
Focus on the practical application of AI, with an emphasis on deploying models and solutions into production environments.

Job Requirements -    Qualifications:

Minimum of 3 years of professional experience in software engineering with a focus on backend development and AI integration.
Strong proficiency in Python.
Hands-on experience working with Language Models, with a primary focus on OpenAI.
Proven ability to develop and optimize prompts for LLMs.
Solid understanding and practical experience with Azure AI services (Document Intelligence, Azure OpenAI, AI Search).
Experience with backend development and API creation.
Proficiency in working with MongoDB.
Exposure to Generative AI concepts and their practical application.
A strong focus on Applied AI, with a demonstrable history of deploying AI solutions into production.
Excellent problem-solving and communication skills.
Ability to work independently and as part of a collaborative team.

Desired Skills & Experience -    Bonus Points:

Experience with DevOps pipelines and deployment processes e.g. GitHub Actions
Experience with Docker and Kubernetes
Infrastructure as code e.g. Terraform
Experience with Authentication and Authorization frameworks
Familiarity with front-end development technologies e.g. React.js (though the primary focus is backend).