The opportunity
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the…
What you'll do
AI UI/UX Design & Implementation: Translate complex generative and agentic AI processes into intuitive, responsive, and engaging front-end interfaces.
Front-End Architecture: Design, build, and maintain front-end UI component libraries. These libraries should be scalable, accessible, and reusable and will be created for generative AI interactions. You will use modern frameworks like React and TypeScript.
Human-AI Interaction Patterns: Prototype and implement novel interaction patterns for conversational AI, agent execution visibility (thought logs, tool calls), prompt systems, and rich dynamic outputs.
Performance & Streaming Optimization: Optimize UI performance for real-time AI responses, managing token streaming latency, async state management, and optimistic UI updates.
Enterprise Grounding & Integration: Connect front-end interfaces to internal services. This includes Retrieval Augmented Generation (RAG) endpoints. It also includes Elasticsearch Relevance Engine (ESRE) and agent orchestration APIs.
User-Centered Collaboration: Partner closely with UX designers, product managers, and AI backend engineers to iteratively test and refine AI workflows based on real user feedback.
What they're looking for
- Accessibility & Design Systems: Ensure all front-end interfaces strictly adhere to web accessibility standards (WCAG) and align seamlessly with Elastic's core design system (EUI).
- AI Observability & UX Analytics: Implement front-end tracking to monitor user satisfaction, prompt effectiveness, interaction latency, and interface usability.
- Documentation: Maintain comprehensive documentation for UI component systems, front-end architecture, and design pattern guidelines.
- Proven Success in AI UX: Recent experience creating user interfaces for GenAI applications is important. This includes working with conversational interfaces, dynamic prompt builders, and complex agent workflows.
