Principal Engineer -Intelligent Document & Context Grounding

About the Role

At UiPath, we believe in the transformative power of automation to change how the world works. We are committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine - people who love being part of a fast-moving, fast-thinking growth company and who care about each other, about UiPath, and about our larger purpose.

The Principal Engineer - Intelligent Document & Context Grounding role is central to this mission. You will own the design and delivery of the core platforms that enable AI agents to understand, retrieve, and reason over enterprise documents at scale. You will architect and build the Intelligent Document Processing and Context Grounding systems that ensure accuracy, security, and performance in production environments. This position requires deep, hands-on engineering leadership to solve some of the most challenging problems in enterprise AI infrastructure. You will raise the quality bar for enterprise AI by focusing on retrieval quality, groundedness, and latency while maintaining strict governance standards. The position demands collaboration across engineering, product, and applied AI teams to turn ambiguous opportunities into reliable production capabilities. You will mentor senior engineers and influence technical direction across multiple organizations while remaining deeply involved in implementation. This is a role for builders who enjoy shipping production AI systems that customers rely on every day.

What You'll Do

Design and Deliver Core AI Services

You will design and deliver the core services that power enterprise document understanding, retrieval, knowledge grounding, and Retrieval-Augmented Generation (RAG) across the UiPath platform. Your work will enable AI agents to ingest, understand, retrieve, and reason over large volumes of enterprise documents while maintaining accuracy, security, governance, and performance.

Own End-to-End Document and Knowledge Systems

• Document ingestion
• Parsing and extraction
• Chunking and embedding
• Indexing
• Retrieval
• Knowledge management
• Evaluation
• Answer grounding

Raise the Quality Bar for Enterprise AI

• Retrieval quality
• Answer quality
• Groundedness
• Attribution
• Latency
• Scalability
• Cost efficiency

You will evaluate emerging techniques, challenge assumptions, and introduce better architectural approaches as AI capabilities continue to evolve in enterprise contexts.

Solve Complex Distributed Systems Problems

You will architect highly available, multi-tenant cloud services that process enormous volumes of enterprise content while maintaining reliability, security, and performance. You will work across:

• Distributed services
• Event-driven architectures
• Search platforms
• Vector databases
• APIs
• Orchestration
• Cloud-native infrastructure

Lead Through Technical Excellence

Principal Engineers at UiPath don't simply review designs - they actively shape them. You will:

• Influence architectural decisions across organizations
• Mentor senior engineers
• Participate in critical design reviews
• Establish engineering standards
• Help teams make thoughtful technical tradeoffs
• Raise the quality of engineering across the organization

Partner Across Engineering, Product, and Applied AI

You will work closely with Product Managers, Applied Scientists, Designers, and Engineering Leaders to turn ambiguous AI opportunities into production capabilities customers rely on every day.

Requirements

Experience and Expertise

We are looking for builders - engineers who enjoy taking complex problems, designing elegant systems, and shipping software that customers depend upon. Successful candidates will 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
• 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 that address security, governance, and compliance needs
• 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

Technologies and Domain Knowledge

• Python
• C#
• Azure (preferred), AWS, or GCP
• Docker
• Kubernetes
• Distributed systems
• Event-driven architectures
• Search platforms
• Vector databases
• LLMs
• Retrieval-Augmented Generation (RAG)
• Embeddings
• OCR
• Intelligent Document Processing
• Knowledge Graphs
• Evaluation frameworks

What Makes Someone Successful Here

The strongest engineers on this team don't simply know AI - they know how to build AI products. They enjoy:

• Solving ambiguous technical problems
• Making thoughtful engineering tradeoffs
• Shipping production systems that customers rely on every day