Principal Software Engineer

UiPath is the leader in the Agentic Automation space. As a Principal Software Engineer on the UiPath Test Cloud team, you will drive the architecture and delivery of platform systems—spanning backend services, AI and agentic capabilities, and end-to-end product experiences—that power the next generation of intelligent, autonomous testing. You will bring deep backend expertise in distributed systems and cloud infrastructure while operating with strong full-stack judgment to shape architectural decisions across the entire engineering stack. Beyond your technical contributions, you will champion the adoption of AI-powered developer tools and coding agents to amplify team productivity—shaping how the engineering organization builds software in an AI-first future.

Responsibilities

Drive the architecture and delivery of platform systems—spanning backend services, AI and agentic capabilities, and end-to-end product experiences; Own the technical vision, architecture, and implementation of large-scale distributed systems that power the Test Cloud platform; Set the multi-quarter technical direction for Test Cloud and drive alignment with adjacent UiPath platform teams; Make architectural calls that span the full stack—API contracts, data flow, state management, real-time/streaming behavior for test execution, performance budgets on both client and server; Partner deeply with product management and design to shape what we build; Own the technical vision for embedding agentic intelligence into test creation, execution, and analysis; Champion the use of coding agents (e.g., Claude Code, GitHub Copilot, Cursor) and AI-assisted workflows to measurably improve team velocity and code quality; Set the engineering bar for the team, mentor senior and mid-level engineers, conduct high-quality design and code reviews; Identify and resolve system bottlenecks, define SLOs, and build for high availability; Evaluate and integrate emerging technologies to continuously evolve the platform; Own software deliverables end-to-end—quality, security, scalability, modifiability, extensibility, and testability

Requirements

Bachelor's/Master's degree in Engineering, Computer Science, or equivalent experience; 13+ years of software engineering experience, with 5+ years focused on distributed systems and backend architecture; Builder’s mindset: Demonstrated track record of taking products and platforms from concept to production at scale; Product sense: Strong customer empathy and product judgment; Strong proficiency in one or more modern backend languages—C# (preferred), Java, Go, or similar, with deep experience building services on frameworks like ASP.NET Core; Full-stack experience: ability to work across backend services and frontend layers (REST/GraphQL APIs, basic UI integration, component contracts); Deep understanding of object-oriented programming, architectural design patterns, system design, and data structures & algorithms; Experience with Angular (preferred), React, TypeScript, or other modern frontend frameworks; Strong grasp of multithreading, asynchronous programming, synchronization, and cloud-native programming models; Hands-on experience with cloud ecosystems: Azure preferred; AWS or GCP also valuable; Experience with serverless and event-driven architectures is highly desirable; Proficiency with containerization and orchestration: Docker, Kubernetes, or equivalent; Hands-on experience with AI coding tools and coding agents (e.g., Claude Code, GitHub Copilot, Cursor, or similar) and a demonstrated ability to integrate these into daily engineering workflows; Experience driving team adoption of AI-powered productivity tools—setting norms, measuring impact, and iterating on usage patterns; Familiarity with modern engineering practices: agile development, CI/CD, DevOps, and infrastructure as code; Excellent verbal and written communication skills; proven success collaborating with globally distributed teams and managing complex, time-bound deliverables; Ability to understand, communicate, and drive complex technical decisions with stakeholders at all levels

Nice to have

Understanding of LLMs, RAG, AI-powered API automation, and agentic workflow design—particularly applied to test generation, self-healing automation, or autonomous quality; Experience with the software testing domain—test automation frameworks (Playwright, Selenium), ALM tools (Jira, Azure DevOps), or CI/CD platform integrations; Experience building or consuming GraphQL APIs; familiarity with API gateways and service mesh patterns; Knowledge of observability tooling: Prometheus, Grafana, OpenTelemetry, distributed tracing; Contributions to developer tooling, internal platforms, or open-source projects; Experience evaluating and implementing AI-driven developer productivity metrics (e.g., DORA metrics augmented by AI tooling adoption)