: Axiata - Power Platform, AI Developer Azure Data Engineer
Number of Positions:
: 2
Primary Skills:
: POWER PLATFORM,COPILOT STUDIO,AZURE AI FOUNDRY,AZURE DATA FABRIC,AZURE AI FOUNDARY
Job Description:
Engagement: 6 Months (Extendable to 12 Months) Location: Kuala Lumpur Sentral (Onsite)
Power Platform & Copilot Studio Developer (4–6 Years)
Summary
This role focuses on designing, developing, deploying, and maintaining enterprise-grade AI solutions using Microsoft Power Platform, Copilot Studio, and Azure AI Foundry. The developer will be directly involved in AI agent creation, workflow automation, and intelligent app development to support business functions in a large enterprise environment.
Key Responsibilities
A. AI & Copilot Studio Development
Build custom AI Agents using Copilot Studio including entities, topics, triggers, system messages, grounding prompts.
Configure generative AI orchestration and use Azure OpenAI/Azure AI Foundry to enhance agent capabilities.
Implement handoff between agents, human approvals, and backend automation.
B. Power Platform Solution Development
Develop Power Apps (Canvas and Model-Driven) with responsive layout, validation rules and integrations.
Build workflows using Power Automate Cloud for business processes across HR, Finance, IT, Operations etc.
Develop attended and unattended automation using Power Automate Desktop (PAD).
Integrate Power Platform solutions with:
Dataverse
SQL / Azure SQL
SharePoint
APIs (REST, OAuth-based)
SAP, Dynamics 365, and external LOB systems (if required)
C. AI Integration & Azure Services
Integrate apps and workflows with Azure AI Foundry, Azure Functions, Logic Apps, API Management.
Create reusable connectors for enterprise applications.
Implement prompt engineering, grounding, retrieval augmentation (RAG), and data governance.
D. Governance, Security & Best Practices
Apply Power Platform ALM, solution layering, environment strategy.
Implement role-based security, DLP policies, auditing and performance optimization.
Follow enterprise architecture and maintain documentation for all solutions.
E. Support, Maintenance & Enhancements
Provide BAU support, troubleshooting, and root-cause analysis for Power Platform solutions.
Conduct knowledge transfer sessions and workshops for internal teams.
Technical Skills Required
Power Apps (Canvas, MDA), Dataverse
Power Automate Cloud + Desktop
Copilot Studio (Custom AI Agent Development)
Azure AI Foundry / Azure OpenAI
REST / JSON / OAuth 2.0 integration
Azure Logic Apps, Azure Functions
Git / DevOps pipelines (ALM)
KQL (basic), Power FX, JSON schema
Understanding of RAG architecture (preferred)
Experience Required
4–6 years in Power Platform development
At least 1–2 enterprise projects using Copilot Studio
Experience integrating AI services into enterprise workflows
Onsite client interaction experience preferred
Expected Deliverables
AI Agent architecture and design documents
Developed agents with workflows, integrations and testing
Power Apps and automated flows with documentation
Integration components and reusable connectors
Deployment packages via solution components
Preferred Certifications
PL-400 (Power Platform Developer)
PL-200 (Functional Consultant)
Azure AI Engineer (AI-102) or Azure Data & AI certification
Soft Skills • Strong communication and client-facing skills. • Ability to collaborate in cross-functional teams. • Proactive problem-solving and self-learning attitude. • Excellent documentation and presentation skills.
Role 2: Azure Data Engineer & Microsoft Fabric Developer (4–6 Years)
Position Summary
This role is responsible for designing and building data pipelines, lakehouses, semantic models, analytics datasets, and dashboards using Microsoft Fabric, Azure Data Engineering services, and Power BI. The developer will support AI agents by supplying structured, clean, governed enterprise data.
Key Responsibilities (Expanded)
A. Microsoft Fabric Development
Build data pipelines using Fabric Data Factory (Copy, Dataflows, Notebooks).
Create and maintain Lakehouses, medallion architecture, Delta tables.
Use Fabric notebooks (PySpark/SQL) for data transformation and cleansing.
Configure Dataflows Gen2 for ingestion from enterprise applications.
Develop Fabric semantic models for downstream AI and BI consumption.
B. Azure Data Engineering
Develop and maintain integrations using:
Azure Data Factory
Azure Databricks (if required)
Azure SQL / SQL Managed Instance
Azure Data Lake Storage Gen2
Build and optimize pipelines with reusable frameworks and orchestration logic.
C. Data Modeling, Analytics & Power BI
Build semantic models for Power BI using star schemas, DAX calculations.
Create enterprise dashboards, Paginated Reports, and real-time datasets.
Ensure data refresh, gateway management, and incremental loading.
D. AI & Agent Enablement
Prepare datasets for Copilot Studio and Azure AI Foundry grounded data.
Build structured knowledge artifacts for RAG-based AI pipelines.
Integrate Fabric datasets with Copilot agents for generative AI use cases.