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UiPath is building the next generation of enterprise AI and automation, where intelligent agents, people, and software work together to solve complex business challenges. This Senior Software Engineer role is a hands-on position focused on developing foundational technologies for the AI platform.
You will work at the intersection of distributed systems, generative AI, and enterprise software. Key responsibilities include:
- Design, develop, and scale services supporting AI agents, evaluations, memory systems, context management, continuous learning, and intelligent document processing
- Build and operate production-grade LLM-powered applications, RAG pipelines, agentic workflows, and document understanding solutions
- Develop highly available, scalable, cloud-native services with strong foundations in asynchronous processing, concurrency, fault tolerance, security, and performance
- Create evaluation frameworks, observability, monitoring, and feedback mechanisms to improve AI quality, accuracy, and reliability
- Build systems for continuous learning across multiple modalities, including agents, ontologies, and deterministic logic
- Own engineering solutions end-to-end from ambiguous requirements through technical design, implementation, testing, deployment, and production operations
- Address enterprise-scale challenges involving multi-tenancy, permissions, retries, idempotency, cost efficiency, latency, and system resilience
- Contribute across the full stack (frontend, backend services, APIs, product-facing experiences)
- Partner with Product Managers, Forward Deployed Engineers, and customer teams to translate business challenges into scalable capabilities
- Influence technical decisions, contribute to architecture discussions, mentor engineers, and establish best practices
Requirements:
- Strong professional software engineering experience building, shipping, and operating complex, production-grade applications, ideally within enterprise SaaS or large-scale cloud platforms
- Deep understanding of distributed systems, backend architecture, microservices, APIs, and cloud-native development
- Demonstrated hands-on experience building and deploying production GenAI applications (LLM-powered products, RAG systems, AI agents, intelligent document processing, or AI-driven enterprise workflows)
- Strong programming skills in Python, C#, or Java, with experience in TypeScript or interest in full-stack development
- Experience designing systems for scalability, reliability, performance, security, and maintainability
- Understanding of practical GenAI engineering challenges (context management, model behavior, retrieval quality, evaluation, latency, cost optimization)
- Ability to navigate ambiguous technical challenges, make sound architectural decisions, and independently deliver high-quality solutions
- Strong product instincts and ability to think beyond individual services to understand end-to-end customer experience
- Excellent collaboration and communication skills across engineering, product, and customer-facing teams
Experience that will set you apart:
- Building AI evaluation frameworks, online/offline evaluation pipelines, or feedback-driven improvement systems
- Agent memory, persistent context, continuous learning, RLHF, or other AI optimization techniques
- Agentic systems involving orchestration, tool calling, planning, state management, or multi-step execution
- Document intelligence (OCR, parsing, chunking strategies, embeddings, vector databases, hybrid search, reranking, grounding)
- Improving reliability and observability of production AI systems (tracing, quality monitoring, failure analysis, evaluation-driven development)
- Building enterprise AI platforms, developer infrastructure, search and retrieval systems, or large-scale cloud services
- Direct customer collaboration on complex business requirements
