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UiPath is seeking a Principal Software Engineer to join the Vertical Solutions team and build the company's AI agentic orchestration platform, recognized as UiPath's Invention of the Year for two consecutive years. This is a high-visibility, high-impact role focused on Act 2 strategy—building infrastructure that enables enterprises to seamlessly orchestrate AI agents, robots, and human-in-the-loop workflows.
You will work with the Maestro backend team to design, develop, and maintain the full-stack orchestration engine powering enterprise AI automation. Day-to-day responsibilities include writing production-quality code leveraging AI coding assistants (Claude, GitHub Copilot), prototyping and validating ideas with real customers, designing evaluations and measuring quality against customer data, and translating customer needs into elegant technical solutions. You'll contribute to building highly scalable, reliable distributed systems that enterprises depend on.
Required qualifications include 13+ years of software engineering experience with 5+ years focused on distributed systems and backend architecture. Strong proficiency in system-level languages (JavaScript, C#, Java) and full-stack capabilities across backend services (REST/GraphQL APIs) and frontend layers (React, TypeScript). Deep expertise in object-oriented programming, architectural design patterns, system design, and data structures. Hands-on experience with cloud ecosystems (Azure, AWS, GCP), containerization (Docker, Kubernetes), and modern engineering practices (agile, CI/CD, DevOps, infrastructure as code).
Critical for this role: production AI systems experience including LLMs, tool-calling, multi-agent architectures, orchestration frameworks (LangGraph, LangChain), structured outputs, and evaluation of model behavior in real-world workflows. Distributed systems expertise designing resilient systems with idempotency, replay ability, state management, and long-running jobs. Strong analytical thinking to reason quantitatively about system quality. Comfort with ambiguity and rapid prototyping. Hands-on experience with AI coding tools and demonstrated ability to integrate them into daily workflows. Experience driving team adoption of AI-powered productivity tools.
Nice-to-have qualifications include healthcare, fintech, or procurement tech systems experience; data science and evaluation; applied ML techniques (classification, anomaly detection, ranking, predictive modeling); large-scale data platforms (Snowflake, columnar warehouses); retrieval-heavy architectures and RAG systems; and experience blending deterministic and probabilistic systems.
