Senior AI Engineer

UiPath UiPath · Enterprise · Bellevue, WA · Engineering

Senior AI Engineer role focused on building and scaling backend services for UiPath's AI platform, specifically for Intelligent Document Processing, Context Grounding, and RAG capabilities. The role involves designing and implementing cloud-native services for document ingestion, extraction, search, retrieval, and AI orchestration, with a strong emphasis on production software and distributed systems.

What you'd actually do

  1. Design, develop, and operate highly scalable backend services that power Intelligent Document Processing, Context Grounding, and Retrieval-Augmented Generation (RAG) capabilities across UiPath's AI platform.
  2. Design and implement cloud-native services capable of processing large volumes of enterprise content while maintaining high availability, reliability, and performance.
  3. Work with modern AI technologies including LLMs, retrieval systems, vector search, and document processing to deliver production capabilities—not research prototypes.
  4. Partner closely with Product Managers, Applied Scientists, Designers, and fellow engineers to turn ideas into production software.
  5. Own features from design through production.

Skills

Required

  • 6+ years of professional software engineering experience
  • Strong backend engineering experience building distributed systems
  • Production experience with Python and/or C#
  • Experience designing scalable APIs and microservices
  • Experience building cloud-native applications on Azure (preferred), AWS, or GCP
  • Strong understanding of distributed systems, concurrency, networking, and software architecture
  • Experience with event-driven systems, messaging, caching, and databases
  • Excellent debugging and problem-solving skills

Nice to have

  • Generative AI
  • Retrieval-Augmented Generation (RAG)
  • LLM-powered applications
  • Semantic search
  • Vector databases
  • Intelligent Document Processing
  • OCR
  • Search infrastructure
  • Knowledge management platforms

What the JD emphasized

  • production software
  • highly scalable backend services
  • cloud-native services
  • high availability, reliability, and performance
  • production capabilities—not research prototypes
  • production software
  • customers rely on every day
  • enterprise scale

Other signals

  • building distributed systems
  • shipping production software
  • AI-powered applications
  • Intelligent Document Processing
  • Context Grounding
  • Retrieval-Augmented Generation (RAG)
  • LLMs
  • vector search
  • knowledge management