Lead architectural design for automation solutions using Microsoft Power Platform and UiPath, focusing on AI workflows, document intelligence, and custom engineering.
Principal Intelligent Automation Architect (AI & RPA)1
Key Responsibilities
- Architectural Leadership: Lead the technical design of enterprise-grade solutions using the Microsoft Power Platform and UiPath ecosystems.
- AI & Agentic Workflows: Build and orchestrate AI Agents and LLM-based workflows that go beyond simple "if-then" logic to handle complex, non-linear business processes.
- Document Intelligence: Implement advanced Document Understanding (UiPath) and AI Builder (Power Apps) models to automate the extraction and processing of semi-structured and unstructured data.
- Custom Engineering: Use Python to extend platform capabilities, create custom APIs, and handle complex data manipulation that standard RPA tools cannot.
- App Development: Design high-performance, user-centric interfaces using Power Apps to act as the front-end for automated workflows.
- Data Strategy: Manage complex data schemas and integration points using SQL Server, ensuring data integrity and high-performance querying for automation logs and business data.
- Solution Governance: Oversee the full ALM (Application Lifecycle Management) process, ensuring robust deployment, security, and scalability of automation assets.
Technical Qualifications
- RPA Platforms - Expert-level proficiency in UiPath (Studio, Orchestrator) and Power Automate (Cloud & Desktop).
- AI & ML | Proven experience with UiPath Document Understanding, Power Platform AI Builder, and building AI Agents.
- Programming | Advanced Python for automation, data science, or API integration.
- Database | Strong SQL skills (Relational design, complex joins, stored procedures).
- Low-Code | Experience building Canvas and Model-driven Power Apps.
- Architecture | Experience as a Solution Architect overseeing infrastructure, security, and scalability.
Preferred Attributes
- A "product mindset"—building tools that are resilient and user-friendly, not just functional.
- The ability to explain complex AI concepts to non-technical stakeholders.
- Experience in a Center of Excellence (CoE) environment.
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