Senior Frontend React Developer
ShelfWarsaw, Poland; Lviv, UkrainePosted 10 March 2026
Tech Stack
Job Description
About Shelf
There is no AI Strategy without a Data Strategy. Getting GenAI to work is mission-critical for most companies, but 90% of AI projects haven't deployed. Why? Poor data quality - it is the #1 obstacle companies have in getting GenAI projects into production.
We've helped some of the best brands like Glovo, Lufthansa, Herbalife, and Nespresso solve their data issues and deploy their AI strategy with Day 1 ROI.
Simply put, Shelf unlocks AI readiness. We provide the core infrastructure that enables GenAI to be deployed at scale. We help companies deliver more accurate GenAI answers by eliminating bad data in documents and files before they go into an LLM and create bad answers.
Shelf is partnered with Microsoft, Salesforce, Snowflake, Databricks, OpenAI and other big tech players who are bringing GenAI to the enterprise.
Our mission is to empower humanity with better answers everywhere.
Senior Frontend React Developer:
As a Frontend Engineer at Shelf, you'll craft the interfaces that make enterprise AI accessible and trustworthy. While others are building chatbots, we're solving the harder problem: how do you build UIs that help users confidently navigate AI-powered systems processing millions of documents, while maintaining enterprise-grade reliability?
You won't just build React components — you'll architect production-ready Next.js applications that handle high-load scenarios with complex states, real-time AI streaming, and multiple layers of enterprise functionality. Every interface decision you make directly impacts how knowledge workers at the biggest companies in the market interact with their most critical information.
This is frontend engineering at its most demanding. You'll tackle challenges like building real-time streaming interfaces for LLM responses, architecting state management for concurrent AI operations across multiple tenants, creating accessible interfaces for complex knowledge graphs with thousands of nodes, and ensuring blazing fast interactions even with petabytes of searchable content. Your components will bridge everything from enterprise authentication systems to cutting-edge AI models, requiring both sophisticated technical skills and sharp product instincts.
We obsess over frontend quality because we're building the trust layer for AI itself. When your interfaces gracefully handle edge cases, provide clear feedback during AI processing, and remain performant under load, you're not just meeting UX standards - you're directly enabling users to trust AI-powered answers and make critical business decisions with confidence.
You'll work on production SSR applications serving thousands of enterprise users, implementing localization for global markets, ensuring accessibility compliance, and maintaining security standards that pass SOC 2 audits. Your code will integrate with our Elasticsearch clusters, DynamoDB tables, and Aurora PostgreSQL databases through the largest park of REST APIs, handling real-time websocket updates for AI streaming and collaborative features.
We're a product company that ships fast without compromising on lasting quality. You'll work alongside proactive, ever-learning engineers who actively use AI coding assistants (OpenAI Codex, Claude Code) to accelerate development. We build custom MCP servers, implement DSPy pipelines for LLM optimization, and experiment with different AI tools for implementation. In our environment, AI isn't just what we build — it's how we build.
The best engineers we know are drawn to problems that matter. If you're excited by the challenge of building interfaces that make the AI revolution actually usable and trustworthy for enterprise users, this role offers the rare combination of technical depth, meaningful impact, and the prestige of solving UX patterns that the industry hasn't figured out yet.
Responsibilities
Design and implement production-ready Next.js SSR applications with complex state management, handling high-load scenari ... (truncated, view full listing at source)
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