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Azure AI Engineer - Pakistan

Summary

Design, build, and deploy AI-powered applications on Azure using Azure AI Services, Azure OpenAI, Copilot Studio, and Power Platform to create chatbots, knowledge assistants, and enterprise copilots.

Position: Azure AI Engineer (LLM & Copilot)

Experience: 5-6 years

About the Role

We are looking for an Azure AI Engineer to design, build, and deploy AI-powered applications on Azure. You will work with Azure AI Services, Azure OpenAI, Copilot Studio, Power Platform, and multi-LLM orchestration to deliver chatbots, knowledge assistants, and enterprise copilots.

You’ll collaborate with data engineers and business teams to create production-ready AI solutions that are scalable, secure, and impactful.

What You’ll Do

  • Build AI applications: chatbots, knowledge assistants, and copilots
  • Implement multi-LLM orchestration across Azure OpenAI, OpenAI, and other providers
  • Work with data engineers to leverage datasets for RAG workflows
  • Integrate AI solutions into business processes using Power Platform
  • Deploy AI apps on Azure (Functions, App Services, AKS, VMs)
  • Implement CI/CD and MLOps pipelines using Azure DevOps or GitHub Actions
  • Monitor performance, reliability, and cost using Azure Monitor and Application Insights
  • Maintain technical documentation and reusable assets
  • Stay current with Azure AI, Copilot, and related technologies

What You Need

  • Bachelor’s or Master’s in Computer Science, AI/ML, or related field
  • 5-6 years of experience in AI, software development, or Azure applications
  • Microsoft certifications: AI-102, AZ-204, DP-100, AZ-400

Hands-on experience with:

  • Azure AI Services and Azure OpenAI
  • Copilot Studio and Power Platform
  • Python or C# for AI/LLM development
  • Deploying applications on Azure
  • Experience with RAG pipelines, vector search, or knowledge integration
  • Understanding of security, governance, and compliance in Azure

Nice to Have

  • Experience integrating AI into enterprise systems (CRM, ERP, LMS)
  • Prompt engineering, fine-tuning, and evaluation of LLMs
  • Infrastructure-as-code: ARM, Bicep, or Terraform
  • Agile/Scrum experience

See also