Azure AI Engineer - Malaysia

Overview

Join to apply for the Azure AI Engineer - Malaysia role at eduCLaaS . This is a remote position. The engineer will be responsible for designing, developing, and deploying AI-powered applications on Microsoft’s Azure ecosystem. This role involves working with Azure AI Services, Azure OpenAI, Microsoft Copilot Studio, MCP (Model Context Protocol) services, and Power Platform integrations to deliver intelligent solutions, such as chatbots, knowledge agents, and adaptive multi-LLM models.

The engineer will collaborate with the team to identify the appropriate technology stack, establish best practices, and contribute to building scalable, secure, and production-ready AI solutions.

Key Responsibilities

• Technology Stack Definition : Identify, evaluate, and recommend Microsoft and Azure-based technologies for AI / LLM development, ensuring scalability and security.
• AI Application Development : Design and implement AI applications such as chatbots, conversational agents, and multi-LLM orchestration using Azure AI and Copilot Studio.
• Multi-LLM Integration : Implement provider-agnostic orchestration and model routing across Azure OpenAI, OpenAI, and other providers (e.g., via Semantic Kernel hybrid model orchestration, LangChain routing, or LiteLLM).
• MCP Integration : Develop and manage MCP (Model Context Protocol) services for orchestrating responses across OpenAI, Azure OpenAI, and other LLM providers.
• End-to-End Deployment : Build, test, and deploy applications on Azure (VMs, AKS, Functions, App Services, etc.), ensuring reliability and high availability.
• Power Platform Integration : Extend applications using Power Apps, Power Automate, and Power Pages to connect AI services with business processes.
• Data & Knowledge Engineering : Integrate Azure Cognitive Services, Azure Search, Dataverse, and vector databases for knowledge ingestion, semantic search, and retrieval-augmented generation (RAG); build and manage Azure Data Factory, Synapse pipelines, or Fabric pipelines for scalable data ingestion and transformation.
• Collaboration & Documentation : Work closely with product managers, solution architects, and business stakeholders to translate requirements into technical solutions. Maintain technical documentation and reusable assets.
• Continuous Improvement : Stay updated with Microsoft’s AI advancements (Azure AI Studio, Fabric, Synapse, Cognitive Services) and incorporate them into project designs.

Requirements

Required Skills & Qualifications

AI-102 – Azure AI Engineer Associate or Azure Solutions Architect

Azure AI Services (Language, Vision, Speech, Cognitive Search, Azure OpenAI)

Preferred Skills

Seniority level

Employment type

Job function

Industries

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