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UiPath is hiring a Principal Software Engineer to build the AI platform powering enterprise agents. This is a hands-on technical leadership role focused on Intelligent Document Processing and Context Grounding—the systems that enable AI agents to ingest, understand, retrieve, and reason over large volumes of enterprise documents while maintaining accuracy, security, governance, and performance.
You will design and deliver core services for document ingestion, parsing, extraction, chunking, embedding, indexing, retrieval, knowledge management, evaluation, and answer grounding. You'll own the technical direction of systems responsible for Retrieval-Augmented Generation (RAG) across the UiPath platform, driving improvements in retrieval quality, answer quality, groundedness, attribution, latency, scalability, and cost efficiency.
This role involves solving difficult distributed systems problems—architecting highly available, multi-tenant cloud services that process enormous volumes of enterprise content while maintaining reliability, security, and performance. You'll work across distributed services, event-driven architectures, search platforms, vector databases, APIs, orchestration, and cloud-native infrastructure.
As a Principal Engineer, you'll influence architectural decisions across organizations, mentor senior engineers, participate in critical design reviews, establish engineering standards, and help teams make thoughtful technical tradeoffs. You'll partner closely with Product Managers, Applied Scientists, Designers, and Engineering Leaders to turn ambiguous AI opportunities into production capabilities.
Successful candidates typically have 10+ years building large-scale software systems, significant experience shipping production AI products, strong backend engineering experience in Python and/or C#, deep understanding of distributed systems and cloud-native architectures, and experience building scalable APIs, microservices, and event-driven systems. You should have strong understanding of modern retrieval systems including RAG, embeddings, vector search, evaluation, and LLM-powered applications, plus experience designing reliable, multi-tenant enterprise platforms. Excellent communication skills and a track record of mentoring engineers and influencing technical direction beyond your immediate team are essential.
