Solution Architect

AI agents are non-deterministic: the same input can produce different outputs across runs. Designing enterprise automation around them takes a different discipline than deterministic RPA; grounded context, dynamic decision logic, and guardrails instead of fixed, scripted paths. This is a forward-deployed, customer-facing engineering role. You will work side by side with enterprise and public sector customers to design, build, and harden agentic workflows in their live environments; combining the hands-on coding of a software engineer, the platform depth of a UiPath specialist, and the end-to-end perspective of a solution architect. You will own the question every customer asks before putting an AI agent into production: “How do we know we can trust it?”

Responsibilities

Own the end-to-end architecture for UiPath automation and agentic programs at customer sites - agents, RPA workflows, integrations, data, and human-in-the-loop steps - and document the trade-offs behind it; Design agentic workflows that combine LLM decision-making with tool and function calling, context grounding, and deterministic fallbacks, so behaviour stays predictable where the business needs it to be; Architect Document Understanding pipelines - extraction, classification, validation - and the Python services that connect them to customer systems; Choose the right GenAI/ML technique per problem; prompting, retrieval and context grounding, or a trained model in AI Center; and set the guardrails, human checkpoints, and escalation paths before go-live; Deploy and operationalize AI agents in production customer environments, including APIs, data pipelines, and integration with existing systems; Act as a trusted technical advisor: translate requirements into architecture and explain design choices, risks, and trade-offs to audiences from engineers to executives; Set the standards, reusable patterns, and design reviews that govern delivery from discovery to hypercare; mentor developers and keep the architecture something customers can operate themselves; Feed field findings such as failure patterns, missing capabilities, design gaps; back into the product roadmap and into reusable assets and accelerators

Requirements

7+ years of hands-on software development in Python, C#, TypeScript, VB.NET, or comparable languages, with production-quality code and solid CS fundamentals; 4+ years building UiPath automation workflows, with working knowledge of Orchestrator, Document Understanding, Action Apps, AI Center, and Insights; Command of UiPath design patterns - Robotic Enterprise Framework, Document Understanding Framework, orchestration processes - and the judgment to know when each fits; Hands-on experience building, deploying, or operating LLM-based agents and agentic workflows (tool/function calling, RAG, multi-step orchestration, LangChain/LangGraph, Model Context Protocol), ideally in production; Working understanding of prompting, grounding, and hallucination - and the judgment to keep agent behaviour inside acceptable bounds once it is live; Proven customer-facing track record in a forward-deployed, professional services, implementation, or consulting role: leading technical workshops, managing stakeholders, delivering under real-world constraints; Technical leadership across globally distributed teams - driving strategy, mentoring engineers, establishing best practices; Experience designing end-to-end solutions across applications, APIs, and automation platforms, with a deep grasp of the design choices that make a system scalable, reliable, and fast; Excellent written and verbal English, with the ability to present complex architecture and delivery risk to executive stakeholders; Degree in Computer Science, Engineering, AI, or a related technical field, or equivalent practical experience