Azure AI Engineer - Malaysia

eduCLaaS; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

An education technology company in Singapore is seeking an Azure AI Engineer to design and develop AI-powered applications on the Azure platform. The role involves collaborating with teams, integrating services, and ensuring scalability and security. Candidates should have a degree in Computer Science or a related field, with 3-6 years of experience in AI/ML development. This position offers opportunities to work on innovative solutions and advance career growth.

Qualifications

• 3-6 years of experience in AI/ML application development focused on Microsoft platforms.
• Strong programming background in Python, C#, or Node.js.
• Hands-on experience with Azure Copilot Studio & Power Platform.

Responsibilities

• Identify and recommend Microsoft technologies for AI development.
• Design and implement AI applications such as chatbots.
• Integrate Azure Cognitive Services for knowledge ingestion and semantic search.

Skills

Experience with Azure AI Services

Programming in Python

MLOps practices

Multi-LLM orchestration knowledge

Enterprise security understanding

Education

Bachelor’s or Master’s degree in Computer Science, AI/ML

Tools

Azure Functions

Cognitive Services

Azure DevOps

Job description

Position Overview

We are seeking a highly skilled Azure AI Engineer to join our team. The engineer will be responsible for designing, developing, and deploying AI‑powered applications on Microsoft’s Azure ecosystem. This role will involve 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 also 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).
• Data Pipelines – 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, and 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

• Education – Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field.
• Experience – 3–6 years of experience in AI/ML application development with focus on Microsoft and Azure platforms.
• Certifications
  • AI-102 – Azure AI Engineer Associate or Azure Solutions Architect
  • DP-100 – Azure Data Scientist Associate
  • AZ-204 – Azure Developer Associate
  • AZ-400 – Azure DevOps Engineer Expert
• Hands‑on experience with
  • Azure AI Services (Language, Vision, Speech, Cognitive Search, Azure OpenAI)
  • Knowledge Microsoft Copilot Studio & Power Platform
  • Azure Functions, AKS (Kubernetes), App Services, Logic Apps
  • Dataverse, Azure SQL, and vector DBs (Pinecone, Cosmos DB with vectors, etc.)
  • Azure Fabric Pipelines
• Programming background – Strong programming background in Python, C#, or Node.js for AI/LLM development.
• Multi‑LLM orchestration – Experience in multi‑LLM orchestration (e.g., MCP services, LangChain, Semantic Kernel).
• MLOps practices – Knowledge of MLOps practices, CI/CD pipelines in Azure DevOps or GitHub Actions.
• Enterprise security – Understanding of enterprise security, compliance, and data governance in Azure.

Preferred Skills

• Certifications in Microsoft Certified: Azure AI Engineer Associate or Azure Solutions Architect.
• Experience integrating AI into enterprise systems (e.g., CRM, ERP, LMS).
• Familiarity with RAG pipelines, prompt engineering, and fine‑tuning LLMs.
• Design and manage Azure core infrastructure (networking, IAM, storage, monitoring) to support AI workloads.
• Implement Azure Monitor, Log Analytics, and Application Insights to track performance, reliability, and cost of AI applications.
• Ensure enterprise‑grade security with Azure Key Vault, Azure AD / Entra ID role‑based access, and policy enforcement.
• Implement infrastructure‑as‑code using ARM templates, Bicep, or Terraform for repeatable deployments.
• Exposure to Agile/Scrum methodologies for project delivery.