Job Title

Azure AI Cloud Developer (Azure AI + Power Platform + Copilot Studio) Full-Time | India with U.S. overlap hours | Immediate Joiner (Preferred) | Chennai Role Overview CXOntology (CXO) is expanding its AI cloud capabilities and enterprise AI solution offerings. We are seeking a hands-on Azure AI Cloud Developer  to design, build, and deploy enterprise-grade AI-powered applications using Microsoft Azure AI services and the Microsoft Power Platform ecosystem . The ideal candidate will have strong experience implementing Azure OpenAI–based copilots, Azure AI Search–enabled knowledge retrieval (RAG), Dataverse-backed applications, Fabric/Data Factory data pipelines, indexing pipelines, and automation workflows using Power Automate and Copilot Studio . This role focuses on building scalable, secure, and production-ready AI assistants and automation solutions integrated with enterprise data platforms and business applications. Key Responsibilities 1. Azure AI & Generative AI Development Design and implement AI-powered enterprise solutions using: Azure OpenAI Service Azure AI Search (vector, hybrid, semantic search) Azure Cognitive Services Azure Machine Learning (as applicable) Responsibilities include: Implement Retrieval-Augmented Generation (RAG) pipelines Build enterprise copilots using Copilot Studio Configure embeddings pipelines Build and maintain enterprise indexing pipelines for knowledge grounding Integrate enterprise knowledge sources Enable grounded AI assistants using Dataverse, Fabric, SharePoint, and CMS platforms 2. Power Platform Application Development Develop intelligent enterprise applications using: Power Apps Power Automate Copilot Studio Dataverse Responsibilities include: Building model-driven and canvas applications Designing workflow automation pipelines Configuring Dataverse tables, relationships, and security roles Integrating Copilot agents with enterprise datasets Implementing approval workflows and orchestration pipelines 3. Azure Data Platform Integration Implement data ingestion and analytics-ready pipelines using: Azure Data Factory Microsoft Fabric (Lakehouse / Warehouse) Azure Data Lake Storage Responsibilities include: Building structured and unstructured ingestion pipelines Designing indexing-ready ingestion architectures Supporting Dataverse analytics integration Enabling semantic indexing pipelines Supporting enterprise knowledge-grounding architecture 4. Azure AI Search & Knowledge Retrieval Architecture Configure Azure AI Search for: vector search semantic ranking hybrid retrieval Responsibilities include: Designing and building enterprise indexing pipelines Creating document ingestion workflows from enterprise sources Implementing metadata-aware indexing strategies Supporting SharePoint/CMS knowledge indexing Enabling search-backed copilots Optimizing retrieval relevance and grounding accuracy 5. Cloud Deployment & Integration Deploy Azure workloads using: ARM templates Bicep Terraform Responsibilities include: Supporting container-based workloads (Container Apps / AKS) Building REST-based integrations Supporting Azure API Management integrations Enabling scalable cloud-native architectures 6. DevOps & ALM Enablement Support deployment automation using: Azure DevOps GitHub Actions Responsibilities include: Managing Power Platform solution lifecycle Supporting Copilot Studio deployment pipelines Implementing environment-based release strategies 7. Security & Governance Implementation Implement enterprise-grade security across: Azure services Dataverse environments Power Platform tenants Responsibilities include: RBAC configuration Managed Identity setup Azure Key Vault integration Responsible AI guardrail implementation 8. Monitoring & Optimization Monitor workloads using: Azure Monitor Application Insights Power Platform analytics Responsibilities include: Improving grounding accuracy Optimizing indexing pipeline performance Optimizing AI workflow performance Supporting SLA-aligned production deployments Required Technical Skills: Azure AI Hands-on experience with: Azure OpenAI Service Azure AI Search Retrieval-Augmented Generation (RAG) Cognitive Services integration Enterprise indexing pipeline implementation Power Platform Strong experience with: Power Apps Power Automate Copilot Studio Dataverse Azure Data Platform Experience with: Azure Data Factory Microsoft Fabric (preferred) Azure Data Lake Storage Development & Integration Experience with: Python or C# REST APIs JSON integrations Event-driven architecture (preferred) DevOps Experience with: Azure DevOps pipelines GitHub Actions Power Platform solution packaging Required Certifications (Mandatory – Any Two) Candidates holding the following combinations of Microsoft certifications (or higher) will be considered an advantage and strongly preferred: Microsoft Certified: Azure AI Engineer Associate (AI-102) Microsoft Certified: Power Platform Developer Associate (PL-400) Microsoft Certified: Azure Developer Associate (AZ-204) Preferred Experience Experience working with: Enterprise Copilot implementations using Copilot Studio Azure AI Search–based knowledge assistants SharePoint / CMS integrations Content automation pipelines Marketing or personalization platforms Dataverse analytics integration with Fabric Enterprise-scale indexing and semantic retrieval architectures Success Metrics Success in this role will be measured by: Deployment of production-ready Copilot agents Implementation of scalable RAG-based knowledge assistants Implementation of enterprise indexing pipelines Integration of Dataverse with Azure AI Search and Fabric Adoption of Power Platform automation across business teams Delivery of enterprise-grade AI-enabled workflows To Apply: Please send your CV and a summary of your relevant experience to