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Microsoft Azure Ai Engineer Certification Jobs (NOW HIRING)

Microsoft certifications such as Azure Developer Associate, Azure AI Engineer Associate, Azure Solutions Architect Expert,AzureDevOps EngineerExpertor related credentials. * Experience with Azure AI ...

Azure AI Architect with M365

Moline, IL · On-site

$57.25 - $74.75/hr

... Microsoft Azure's ecosystem. This senior role requires deep expertise in AI/ML architectures ... Implement prompt engineering, fine-tuning , and retrieval mechanisms for improved AI performance

AI Engineer II

Chicago, IL · On-site

$116K - $144K/yr

Bachelor's degree in Computer Science, Engineering, Data Science, or a related field; advanced degree or certifications (e.g., Microsoft Certified: Azure AI Engineer Associate) are a plus.

... Microsoft Azure's AI ecosystem, working across various sectors to deliver innovative solutions ... Preferred : • Technical certifications in Azure (e.g., AZ-900, AZ-204, AZ-305, AZ-102) are highly ...

AI Engineer II

Houston, TX · On-site

$116K - $144K/yr

Bachelor's degree in Computer Science, Engineering, Data Science, or a related field; advanced degree or certifications (e.g., Microsoft Certified: Azure AI Engineer Associate) are a plus.

AI Engineer II

Houston, TX · On-site

$116K - $144K/yr

Bachelor's degree in Computer Science, Engineering, Data Science, or a related field; advanced degree or certifications (e.g., Microsoft Certified: Azure AI Engineer Associate) are a plus.

... power of Microsoft Azure's AI ecosystem. This role is ideal for a seasoned engineer with deep ... Technical certifications in Azure (e.g., AZ-900, AZ-204, AZ-305, AZ-102) are highly desirable.

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Microsoft Azure Ai Engineer Certification information

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$25

$53

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How much do microsoft azure ai engineer certification jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for microsoft azure ai engineer certification in the United States is $53.63, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $62.26 per hour, depending on experience, location, and employer.

What is Microsoft Azure AI Engineer Certification?

Microsoft Azure AI Engineer Certification, specifically the Azure AI Engineer Associate (Exam AI-102), validates your expertise in designing and implementing AI solutions on Microsoft Azure. It demonstrates your ability to use Azure Cognitive Services, Azure Machine Learning, and Knowledge Mining to build, manage, and deploy AI solutions that leverage natural language processing, computer vision, conversational AI, and other machine learning techniques. Achieving this certification can help you advance your career in AI and cloud technologies by proving your skills to employers and peers.

What are the key skills and qualifications needed to thrive as a Microsoft Azure AI Engineer, and why are they important?

To thrive as a Microsoft Azure AI Engineer, you need a solid background in computer science, machine learning, and cloud computing, typically supported by a relevant degree and the Microsoft Certified: Azure AI Engineer Associate certification. Proficiency with Azure Machine Learning, Cognitive Services, Python, and AI development frameworks is essential. Strong analytical thinking, collaboration, and problem-solving skills help you design and implement effective AI solutions. These skills ensure you can create, deploy, and manage AI solutions on Azure that meet business needs securely and efficiently.

What are the typical challenges faced by professionals preparing for the Microsoft Azure AI Engineer Certification, and how can they overcome them?

Preparing for the Microsoft Azure AI Engineer Certification often involves mastering a broad range of AI and cloud concepts, which can be challenging for those without prior experience in both areas. Candidates may struggle with understanding Azure-specific services, designing AI solutions, and integrating machine learning models into cloud environments. To overcome these challenges, it's helpful to follow structured learning paths, engage in hands-on labs, participate in study groups, and review official Microsoft documentation regularly. Leveraging practice exams and real-world projects can also boost confidence and readiness for the certification.

What is the difference between Microsoft Azure Ai Engineer Certification vs Data Scientist?

AspectMicrosoft Azure Ai Engineer CertificationData Scientist
Required CredentialsAzure AI certifications, cloud knowledgeStatistics, programming, data analysis
Work EnvironmentCloud platforms, AI solutions on AzureData analysis, research, modeling
Industry UsageAI development, cloud services, enterprise solutionsData analysis, research, predictive modeling

The Microsoft Azure Ai Engineer Certification focuses on designing and implementing AI solutions using Azure cloud services, emphasizing cloud skills and AI deployment. In contrast, Data Scientists analyze data, build models, and derive insights, often using various tools and programming languages. Both roles are vital in AI and data-driven industries but differ in their core focus and skill sets.

Is Microsoft Azure AI Engineer Certification worth it?

The Microsoft Azure AI Engineer Certification validates skills in designing and implementing AI solutions using Azure services, which can enhance job prospects and earning potential in AI and cloud roles. It demonstrates proficiency with tools like Azure Machine Learning and cognitive services, making certified professionals more competitive in the job market.

What jobs can I get with Microsoft Azure AI Engineer Certification?

With a Microsoft Azure AI Engineer Certification, you can pursue roles such as AI Engineer, Machine Learning Engineer, Data Scientist, or Cloud Solutions Architect. These positions involve designing and implementing AI solutions using Azure services, requiring skills in machine learning, data analysis, and cloud computing environments.

What are popular job titles related to Microsoft Azure Ai Engineer Certification jobs?

For Microsoft Azure Ai Engineer Certification jobs, the most frequently searched job titles are:

Infographic showing various Microsoft Azure Ai Engineer Certification job openings in the United States as of September 2026, with employment types broken down into 2% As Needed, 73% Full Time, 17% Part Time, and 8% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $111,552 per year, or $53.6 per hour.

Senior Consultant, Microsoft Full Stack & AI Engineering

Redmond, WA • On-site

Artic Consulting
IT Services • 1 - 10 employees

$125K - $150K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 9 days ago


Job description

About Artic Consulting 

Artic Consulting is a Microsoft-focused consulting partner helping clients modernize applications, data platforms, cloud operations, and business workflows through Microsoft cloud, AI, automation, and enterprise application engineering solutions. 

Position Summary 

Artic Consulting is seeking a Senior Consultant, Microsoft Full Stack & AI Engineering to design, build, and support secure, scalable, AI-first, cloud-native enterprise applications using the Microsoft technology ecosystem. This role combines senior full stack engineering, Azure application development, AI agent development, AI-enabled feature delivery, and client-facing consulting responsibilities. 

The successful candidate will work with cross-functional teams and U.S.-based stakeholders to translate business requirements into reliable application solutions, integrate AI capabilities where appropriate, and maintain high standards for code quality, security, data privacy, maintainability, and responsible AI implementation. 

Key Responsibilities :

  • Design, develop, test, and maintain full stack application features using Microsoft technologies including .NET, C#, ASP.NET Core, Web API, Entity Framework, SQL Server or Azure SQL, JavaScript, TypeScript, Angular or React. 
  • Build secure, scalable, maintainable cloud-based application solutions using Microsoft Azure services such as Azure Functions, App Services, Blob Storage, Azure Data Factory, Logic Apps, Microsoft Entra ID, Azure DevOps, and related services. 
  • Configure and manage Azure DevOps to support GitHub automated releases, including workflows, team ceremonies, and queries. 
  • Integrate AI-enabled capabilities into enterprise applications, including intelligent search, document and content analysis, recommendations, workflow automation, chat or assistant experiences, and AI-assisted user experiences where appropriate. 
  • Apply practical AI engineering patterns such as prompt engineering, retrieval-augmented generation (RAG), embeddings, vector search, model-output evaluation, guardrails, and human-in-the-loop review for production-oriented features. 
  • Design and develop AI agents and copilots using Azure AI Foundry, Azure OpenAI, Semantic Kernel, Microsoft Copilot Studio, or equivalent frameworks.  
  • Implement enterprise AI solutions using Azure AI Search, vector search, prompt engineering, and Model Context Protocol (MCP) integrations with enterprise systems and APIs.  
  • Collaborate with stakeholders to identify practical AI use cases, clarify requirements, assess technical feasibility, and deliver secure, scalable solutions aligned to business outcomes. 
  • Use AI-assisted engineering tools, including GitHub Copilot or similar tools, responsibly to improve development productivity while maintaining code review, security, privacy, and quality standards. 
  • Design and optimize relational database structures and SQL queries, including performance tuning, indexing, data integrity controls, and support for application releases. 
  • Deploy and manage cloud-native applications using Docker, Azure Container Apps, Kubernetes (AKS), and Infrastructure as Code (Bicep or Terraform).  
  • Monitor application and AI solution performance using Azure Monitor, Application Insights, and OpenTelemetry. 
  • Participate in Agile delivery activities including sprint planning, estimation, backlog refinement, demos, release planning, and retrospectives. 
  • Troubleshoot application, integration, database, and cloud issues; identify root causes; implement practical fixes; and document resolution steps. 
  • Create and maintain technical documentation including architecture notes, design decisions, API specifications, implementation notes, release documentation, and operational runbooks. 
  • Work effectively with business analysts, UI/UX designers, QA engineers, DevOps resources, project managers, client stakeholders, and other developers to deliver high-quality solutions. 
  • Mentor junior developers by providing technical guidance, code review feedback, design-pattern coaching, and support for engineering best practices. 

Required Qualifications :

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience. 
  • Experienced professional full stack application development experience in enterprise, product, or client-facing software environments. 
  • Strong hands-on experience with .NET, C#, ASP.NET Core, Web API, Entity Framework, SQL, HTML, CSS, JavaScript or TypeScript, and Angular or React. 
  • Experience designing and delivering cloud-based solutions using Microsoft Azure services and secure identity patterns, including Microsoft Entra ID or equivalent identity platforms. 
  • Practical experience integrating AI capabilities into applications using Azure AI services, Azure OpenAI Service, LLM APIs, GitHub Copilot, or equivalent AI-assisted engineering tools. 
  • Hands-on experience with Azure AI Foundry, Azure AI Search, Semantic Kernel, AI agent development, and enterprise AI integrations. 
  • Working knowledge of prompt engineering, RAG, embeddings, vector search, responsible AI practices, data privacy, security, and validation of AI-generated outputs. 
  • Experience implementing AI evaluation, prompt optimization, model governance, and AI application security best practices. 
  • Experience with relational database design, SQL query development, performance optimization, transaction handling, and data integrity controls. 
  • Experience with CI/CD, source control, work tracking, release coordination, and engineering practices using Azure DevOps, GitHub, Jira, or similar tools. 
  • Identify opportunities to improve processes, drive innovation, and adopt emerging technologies that deliver client business value. 
  • Strong analytical, troubleshooting, documentation, collaboration, and ownership skills. 

Preferred Qualifications:

  • Microsoft certifications such as Azure Developer Associate, Azure AI Engineer Associate, Azure Solutions Architect Expert, Azure DevOps Engineer Expert or related credentials. 
  • Experience with Azure AI Foundry, AI Agent Service, Prompt Flow, Semantic Kernel, Azure AI Search, Microsoft Fabric, Copilot Studio, Microsoft 365 Copilot extensibility, and enterprise AI governance.  
  • Experience with Model Context Protocol (MCP), GitHub Copilot Enterprise, Azure API Management, Azure Monitor, and Application Insights. 
  • Prior consulting experience, including client discovery, solution estimation, delivery planning, technical presentations, and stakeholder management. 
  • Experience working with secure coding, accessibility, privacy-aware development, release governance, and compliance-conscious engineering practices. 
  • Benefits 
  • Competitive compensation and performance-based opportunities, subject to company policy and role eligibility. 
  • Flexible work practices, professional development resources, certification support, and training aligned to business needs. 
  • Collaborative team environment with exposure to Microsoft-focused technology projects and U.S.-based client work. 
  • Benefits may include medical, dental, vision, life insurance, paid time off, retirement benefits, and other benefits subject to role location, plan terms, and applicable policy. 

Equal Employment Opportunity :

Join Artic and you will benefit from outstanding professional support and investment in your development.  You will have the opportunity to learn from and be coached by the best in the business – supportive leaders and colleagues who can pass on their industry, technical, and functional expertise.  

This also includes medical, dental, vision, and life insurance benefits, 401k, vacation, training expenses, and training budget.  

Added pay band: 

$125,000 - $150,000 USD annual base salary, plus performance-based incentives and benefits where applicable. 

 
 

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