Principal Intelligent Automation Architect (AI & RPA)

Posted:
2/9/2026, 4:00:00 PM

Location(s):
Maharashtra, India ⋅ Pune, Maharashtra, India

Experience Level(s):
Expert or higher ⋅ Senior

Field(s):
Software 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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