Principal Intelligent Automation Architect - AI and Robotic Process Automation

Principal Intelligent Automation Architect (AI & RPA)

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.

Experience Level

Senior Level