Principal Engineer -intelligent Document & Context Grounding

UiPath UiPath · Enterprise · Bellevue, WA · Engineering

Principal Engineer role focused on building the AI platform for enterprise agents, specifically Intelligent Document Processing and Context Grounding. The role involves designing and delivering core services for document understanding, retrieval, knowledge grounding, and RAG, while improving quality, scalability, and performance. It requires strong backend engineering, distributed systems expertise, and experience shipping production AI products.

What you'd actually do

  1. Design and deliver the core services that power enterprise document understanding, retrieval, knowledge grounding, and Retrieval-Augmented Generation (RAG) across the UiPath platform.
  2. Drive improvements in: retrieval quality, answer quality, groundedness, attribution, latency, scalability, cost efficiency
  3. Architect highly available, multi-tenant cloud services that process enormous volumes of enterprise content while maintaining reliability, security, and performance.
  4. Influence architectural decisions across organizations
  5. Work closely with Product Managers, Applied Scientists, Designers, and Engineering Leaders to turn ambiguous AI opportunities into production capabilities customers rely on every day.

Skills

Required

  • 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
  • Experience building scalable APIs, microservices, and event-driven systems
  • Strong understanding of modern retrieval systems including RAG, embeddings, vector search, evaluation, and LLM-powered applications
  • Experience designing reliable, multi-tenant enterprise platforms
  • Excellent communication skills and the ability to explain complex technical concepts clearly
  • A track record of mentoring engineers and influencing technical direction beyond their immediate team

Nice to have

  • Azure (preferred), AWS, or GCP
  • Docker
  • Kubernetes
  • Knowledge Graphs
  • OCR
  • Intelligent Document Processing

What the JD emphasized

  • repeatedly shipped production AI systems
  • building the next generation of enterprise AI
  • understand business context, reason over enterprise knowledge, and deliver trustworthy outcomes at scale
  • ingest, understand, retrieve, and reason over large volumes of enterprise documents
  • maintaining accuracy, security, governance, and performance
  • shipping software that customers depend upon
  • Significant experience shipping production AI products
  • Strong understanding of modern retrieval systems including RAG, embeddings, vector search, evaluation, and LLM-powered applications
  • building software that thousands of organizations rely on every day

Other signals

  • Build production AI systems
  • Raise the quality bar for enterprise AI
  • Solve difficult distributed systems problems
  • Lead through technical excellence
  • Partner across Engineering, Product, and Applied AI