Power Platform Engineer (Low-Code Automation & Document Intelligence)Location Hyd/blrYears of Experience 5 to 10 years in software development, application engineering, or process automation.Power Platform Build Focus Minimum 3+ years of hands-on experience designing complex Power Automate Cloud Flows, Power Automate Desktop (RPA) tasks, and custom Canvas/Model-Driven Power Apps. SummaryRole Objective Develop the low-code automation flows, user-facing applications, Robotic Process Automation (RPA) queues, and core document intelligence models that power the solution. In addition to designing the main ingestion paths and exception-handling portals, you will own the training and deployment of all out-of-the-box document processing and classification tools.Core Responsibilities Train and fine-tune AI Builder Document Classifier models across the catalog of 140+ structured document templates.Configure, build, and optimize template-specific extraction schemas using AI Builder Document Processors.Implement and configure Azure Document Intelligence (Read)
as a high-fidelity OCR fallback engine, mapping text arrays cleanly into the ingestion pipeline.Develop automated ingestion workflows using Power Automate Cloud Flows across email, SharePoint, and SFTP endpoints.Build the Model-Driven Power App human-in-the-loop (HITL) exception review interface, rendering side-by-side data comparisons and original document views.Configure Power Automate Desktop (RPA) tasks to handle secure write-backs to core transactional systems.Design and deploy central performance dashboard metrics in Power BI.Technical Requirements &
Key Skills Power Platform Native Deep experience with Dataverse, Power Automate (Cloud & Desktop), Canvas/Model-Driven Apps, and the Power Apps Component Framework (PCF).No-Code/Low-Code AI Expert-level mastery of AI Builder (Document Processing, Custom Classifiers) and direct integration with Azure Document Intelligence.Relational Data Engineering Robust skills configuring relationships, security structures, and business rules within Microsoft Dataverse.