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Azure AI Engineer

Design and implement AI solutions on Azure using computer vision, natural language processing, knowledge mining, and document intelligence services.

⏱️ 3-5 months
📊 4 Phases
🎓 AI-102 Certification
💼 Mid-Level
🎯 Mid-Level Role

What Does an Azure AI Engineer Do?

Azure AI Engineers design, build, and deploy intelligent applications using Azure Cognitive Services and Azure AI services. You'll implement computer vision solutions, build natural language processing applications, create knowledge mining pipelines, and integrate AI capabilities into modern cloud applications to solve real-world business problems.

Is This Roadmap For You?

📜 Recommended Certification Path

AI-900

Azure AI Fundamentals

Recommended
→

AI-102

Azure AI Engineer

After Phase 4

📋 AI-102 Exam Syllabus Overview

The official Microsoft AI-102 exam tests your knowledge across four key skill areas:

25-30%
Plan and manage an Azure AI solution
  • Select appropriate Azure AI services
  • Manage Azure Cognitive Services
  • Monitor AI services
  • Plan for responsible AI
30-35%
Implement computer vision solutions
  • Analyze images with Computer Vision
  • Implement Custom Vision solutions
  • Detect and analyze faces
  • Read text with OCR
25-30%
Implement natural language processing solutions
  • Analyze text with Language service
  • Build question answering solutions
  • Build conversational language understanding models
  • Create custom named entity recognition
10-15%
Implement knowledge mining and document intelligence solutions
  • Implement Azure Cognitive Search
  • Create enrichment pipelines
  • Implement Form Recognizer solutions
  • Manage search indexes

🚀 Start Here

If you're new to Azure AI:

→Begin with Phase 1: Master Azure AI Fundamentals (expand below)

→Ensure you have programming experience in Python or C#

→Complete Azure AI Fundamentals (AI-900) if new to Azure AI

→Focus on one phase at a time — finish it completely before moving forward

Already have AI or development experience?

→Jump to the phase that matches your current skill level

1
Master Azure AI Fundamentals
3-4 weeks
2-3 hrs/day
▼
✅ Core Skills = Must complete to move forward | ◻ Optional = Nice-to-have if time permits
CORE
🧠 Azure Cognitive Services

Service overview, authentication, endpoints, API key management

CORE
🏗️ AI Architecture

AI service selection, responsible AI principles, solution design

CORE
🐍 Python/C# SDKs

Azure AI SDK setup, authentication patterns, async programming

CORE
🌐 REST APIs

HTTP methods, JSON handling, API integration patterns

OPTIONAL
📊 Azure ML Basics

Machine learning fundamentals, model training concepts

🎯 Learning Actions

📚 Learn
Microsoft Learn AI fundamentals paths
🛠️ Practice
Create Cognitive Services resources
✅ Prove
Call a Cognitive Service using REST API
2
Build Computer Vision Solutions
4-5 weeks
2-3 hrs/day
▼
✅ Core Skills = Must complete to move forward | ◻ Optional = Nice-to-have if time permits
CORE
🖼️ Custom Vision

Image classification, object detection, model training and deployment

CORE
👤 Face API

Face detection, verification, identification, face attributes

CORE
📝 OCR

Text extraction, Read API, handwriting recognition, document analysis

CORE
🎥 Video Analysis

Video indexer, motion detection, content moderation

OPTIONAL
🔍 Computer Vision

Image analysis, spatial analysis, advanced features

🎯 Learning Actions

📚 Learn
Microsoft Learn Computer Vision modules
🛠️ Practice
Build image classification model
✅ Prove
Deploy custom vision model to production
3
Implement NLP Solutions
3-4 weeks
2-3 hrs/day
▼
✅ Core Skills = Must complete to move forward | ◻ Optional = Nice-to-have if time permits
CORE
🗣️ Language Understanding

Intent recognition, entity extraction, conversational AI models

CORE
📊 Text Analytics

Sentiment analysis, key phrase extraction, language detection

CORE
❓ QnA Maker

Knowledge base creation, question answering, FAQ automation

CORE
🤖 Bot Framework

Conversational bots, dialog management, channel integration

OPTIONAL
🔤 Translator

Text translation, document translation, custom models

🎯 Learning Actions

📚 Learn
Microsoft Learn NLP modules
🛠️ Practice
Build conversational bot with QnA
✅ Prove
Deploy intelligent chatbot solution
4
Create Knowledge Mining Solutions
2-3 weeks
2 hrs/day
▼
✅ Core Skills = Must complete to move forward | ◻ Optional = Nice-to-have if time permits
CORE
🔎 Azure Cognitive Search

Search indexes, indexers, skillsets, semantic search

CORE
📄 Form Recognizer

Document analysis, custom models, receipt/invoice processing

CORE
🔗 Document Intelligence

Layout analysis, key-value extraction, table extraction

CORE
⚙️ Enrichment Pipelines

Custom skills, AI enrichment, knowledge store

OPTIONAL
📈 Advanced Search

Scoring profiles, analyzers, filters, facets

🎯 Learning Actions

📚 Learn
Microsoft Learn Knowledge Mining modules
🛠️ Practice
Build search solution with enrichment
✅ Prove
Practice AI-102 questions

🎓 Target Certification

AI-102: Designing and Implementing a Microsoft Azure AI Solution

This certification validates your expertise in building, managing, and deploying AI solutions using Azure AI services. It demonstrates your ability to implement computer vision, natural language processing, and knowledge mining solutions.

Practice AI-102 Questions

🎯 You're Job-Ready When You Can:

✅ Build Computer Vision Apps

Create custom image classification and object detection models

✅ Implement NLP Solutions

Build conversational bots and language understanding models

✅ Create Search Solutions

Deploy Azure Cognitive Search with AI enrichment pipelines

✅ Process Documents

Extract data from forms and documents using Form Recognizer

✅ Manage AI Services

Deploy, monitor, and secure Azure Cognitive Services

✅ Pass AI-102 Certification

Validate your knowledge with Microsoft's Azure AI Engineer credential