Senior xEngineer (Backend Oriented) - User Voice

Wix makes it possible for anyone to succeed online. Since 2006, we’ve grown to around 4,400 employees in 22 countries, launched over 40 products, and serve over 299 million users and their visitors worldwide. At Wix, we push you to innovate and evolve in non-traditional ways. We operate in collaborative, high-performing teams, building cutting-edge products and leveraging AI to redefine how our users create, manage and grow their dreams online.

Although we’re already industry leaders in web creation and business, our work is nowhere near done. Our goal is to become the main engine of the Internet so we can create a more open web for all.

We're looking for an experienced xEngineer with a backend orientation to join the User Voice team.

User Voice is the platform that lets Wix hear its users at scale. It ingests feedback from millions of user interactions and transforms it into actionable insights through a multi-stage AI pipeline - combining natural language understanding, semantic representation and retrieval, and large-scale unsupervised clustering. The platform is expanding rapidly - onboarding new feedback channels and new types of user signals - and you'll be a driving force in shaping the backend architecture behind that growth, powering the insights that shape product roadmaps across Wix.

Responsibilities

Design and evolve the platform's backend together with the team - a large-scale, event-driven microservices system processing feedback in real time and in batch; Lead the expansion to new feedback channels and new types of insight, shaping how each one is brought into the platform reliably and at quality; Build and improve the AI pipeline stages that turn raw feedback into structured, trustworthy insights - from LLM-based information extraction to semantic clustering; Help establish evaluation as part of how the team ships - automated quality measurement, regression evaluation on model and prompt changes, and readiness criteria for new feedback channels; Collaborate with data engineering, data science, and product to take capabilities from idea to production; Treat reliability, scalability, and cost as core features of the platform

Requirements

5+ years of software engineering experience with a strong backend orientation - designing and owning distributed, event-driven systems at scale; Hands-on experience building LLM-based systems in production - extraction pipelines, structured outputs, prompt and model lifecycle - and dealing with their real-world failure modes: quality, cost, and latency; Strong prompt engineering skills - designing, iterating, and versioning prompts for reliable, structured results at scale; Experience evaluating AI systems - defining quality metrics, building evaluation datasets, benchmarking and selecting models per task, and validating changes before they ship; Working understanding of applied ML in production - embeddings, vector search, and clustering algorithms; Solid grasp of large-scale data processing: pipelines, backfills, reprocessing, and warehouse-scale SQL

Nice to have

JVM-language experience (Scala, Java, or Kotlin) and solid Python; Experience with vector search engines or RAG architectures; Background in voice-of-customer, feedback analytics, or similar insight products