Azure AI Engineer (Power Platform and Microsoft Fabric) - remote

6 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Full Time

Job Description

Overview

Azure AI Engineer

You’ll work on solutions like AI copilots, chatbots, and knowledge assistants that connect data, automation, and intelligence across business systems.

Job Responsibilities

  • Build AI Applications

    – Develop chatbots, copilots, and intelligent apps using

    Azure AI Services

    ,

    Copilot Studio

    , and

    Power Platform

    tools.
  • Integrate Power Platform

    – Connect AI features into

    Power Apps

    ,

    Power Automate

    , and

    Power Pages

    to boost productivity and decision-making.
  • Use Microsoft Fabric

    – Design and manage

    Fabric pipelines

    for data ingestion, transformation, and analytics to power AI and business insights.
  • Orchestrate Multi-LLM Models

    – Use

    Azure OpenAI

    ,

    Semantic Kernel

    , or

    LangChain

    to combine and optimize multiple AI models.
  • Deploy & Scale

    – Launch applications on

    Azure Functions

    ,

    AKS

    , or

    App Services

    , ensuring high performance and security.
  • Collaborate & Improve

    – Work with solution architects and product teams to continuously adopt the latest Microsoft AI, Fabric, and Copilot innovations.

Requirements

  • Degree in Computer Science, AI/ML, or related field.
  • Microsoft Certifications (AI-102, DP-100, AZ-204, AZ-400).
  • 3–6 years’ experience developing AI or data-driven applications on

    Microsoft Azure

    .
  • Hands-on experience with:
  • Azure AI Services

    (Language, Vision, Speech, Cognitive Search, OpenAI)
  • Power Platform

    (Power Apps, Power Automate, Dataverse)
  • Microsoft Fabric or Azure Data Factory

    for data pipelines
  • Programming in

    Python, C#

    , or

    Node.js

  • Understanding of

    MLOps

    ,

    DevOps

    , and

    data governance

    on Azure.
  • Experience with

    RAG

    ,

    prompt engineering

    , or

    LLM fine-tuning

    .
  • Familiarity with

    Azure Monitor

    ,

    Bicep/Terraform

    , and

    Agile

    project delivery.

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