Senior Software Engineer -AI

UiPath•Bellevue, WA

1d•$180,000 - $230,000

About The Position

UiPath is seeking a Senior Software Engineer to build foundational technologies for its enterprise AI platform. The role works at the intersection of distributed systems, generative AI, and enterprise software, developing capabilities that help AI agents and intelligent applications operate reliably, learn continuously, and deliver business outcomes at scale. This is a hands-on engineering position for someone who enjoys solving difficult technical problems, working through ambiguity, and building production-ready AI products. The engineer will contribute to platform capabilities including AI evaluations, agent memory, continuous learning, orchestration, intelligent document processing, and retrieval systems. The role covers the full engineering lifecycle, from technical design and implementation through testing, deployment, and production operations, and includes collaboration with product, customer-facing, and engineering teams.

Requirements

Professional software engineering experience building, shipping, and operating complex, production-grade applications; enterprise SaaS or large-scale cloud platform experience is preferred.
Deep understanding of distributed systems, backend architecture, microservices, APIs, and cloud-native development.
Hands-on experience building and deploying production GenAI applications, such as LLM-powered products, RAG systems, AI agents, intelligent document processing, or AI-driven enterprise workflows.
Strong programming skills in Python, C#, or Java, and experience with TypeScript or interest in developing full-stack capabilities.
Experience designing systems for scalability, reliability, performance, security, and maintainability.
Understanding of practical GenAI engineering challenges, including context management, model behavior, retrieval quality, evaluation, latency, and cost optimization.
Ability to navigate ambiguous technical challenges, make sound architectural decisions, and independently deliver high-quality solutions.
Strong product instincts and ability to consider the end-to-end customer experience.
Excellent collaboration and communication skills, including effectiveness across engineering, product, and customer-facing teams.

Nice To Haves

Experience building AI evaluation frameworks, online or offline evaluation pipelines, or feedback-driven improvement systems.
Experience with agent memory, persistent context, continuous learning, reinforcement learning from human feedback (RLHF), or other AI optimization techniques.
Experience developing agentic systems involving orchestration, tool calling, planning, state management, or multi-step execution.
Deep experience with document intelligence, including OCR, parsing, chunking strategies, embeddings, vector databases, hybrid search, reranking, and grounding.
Experience improving production AI reliability and observability through tracing, quality monitoring, failure analysis, and evaluation-driven development.
Experience building enterprise AI platforms, developer infrastructure, search and retrieval systems, or large-scale cloud services.
Experience collaborating directly with customers to translate complex business requirements into production software.

Responsibilities

Design, develop, and scale services supporting AI agents, evaluations, memory, context management, continuous learning, and intelligent document processing.
Build and operate LLM-powered applications, retrieval-augmented generation pipelines, agentic workflows, and document-understanding solutions.
Develop highly available, scalable, cloud-native services with asynchronous processing, concurrency, fault tolerance, security, and performance in mind.
Create evaluation frameworks, observability, monitoring, and feedback mechanisms to improve AI quality, accuracy, reliability, and performance.
Build continuous-learning systems across multiple modalities, including agents, ontologies, and deterministic logic.
Own engineering solutions end to end, from ambiguous requirements through design, implementation, testing, deployment, and ongoing production operations.
Address enterprise-scale challenges including multi-tenancy, permissions, retries, idempotency, cost efficiency, latency, and resilience.
Contribute across frontend, backend services, APIs, and product-facing experiences.
Collaborate with Product Managers, Forward Deployed Engineers, customers, and other engineering teams to turn customer challenges into scalable product capabilities.
Influence technical decisions, contribute to architecture discussions, mentor engineers, and establish best practices for reliable AI-powered software.