[Remote] AI Experience Engineer

Note: The job is a remote job and is open to candidates in USA. JD Power powers auto-related decisions through proprietary data, advanced analytics, industry expertise, and connected workflows. The AI Experience Engineer will build full-stack, human-facing interfaces for AI-powered systems, including agent observability tools, reusable design-system components, evaluation interfaces, and accessible production-quality experiences for technical and business stakeholders.

Responsibilities

• Own the full-stack design and engineering quality for all Innovation Crew pilots and prototypes: take concepts from brief or wireframe through backend service, API integration, and polished production-quality interface; ensure every deliverable shown to engineering leadership or business stakeholders is visually consistent, accessible, and immediately legible to non-technical audiences
• Design the human-on-the-loop interaction patterns for agentic systems: build the interfaces that let engineers and reviewers inspect agent traces, audit reasoning outputs, adjust parameters, and surface anomalies, with the goal of keeping humans informed and in control without making them a bottleneck at every step. The standard is observable by default, not approved at every gate
• Build and maintain a shared design system and component library for Innovation Crew outputs, including AI-specific components: streaming output displays, agent status and progress indicators, trace inspection views, confidence surfaces, and human-review interfaces that Launch Lab can consume directly when taking pilots to production
• Define the UX standards and interaction vocabulary for the AI Assistants and Copilots capability pillar: contextual AI assistance interfaces, real-time knowledge retrieval surfaces, AI-generated content displays, and role-specific intelligence dashboards - establishing the patterns JD Power will use as these capabilities scale
• Conduct lightweight user research and usability testing with internal stakeholders and business unit partners; bring user signal into the Innovation Crew design process early enough to shape what gets built, not just how it looks; partner with the Principal AI Engineer to design evaluation interfaces and agent observability dashboards that make model behavior and trace output readable for human reviewers
• Champion WCAG accessibility standards and performance engineering across all Innovation Crew deliverables; apply JD Power brand guidelines to any output shown externally; contribute UX and frontend technology evaluations to the Emerging Technology Radar process and propose directional Architecture Decision Records for AI interaction patterns the Innovation Crew adopts

Skills

• Full-stack engineering with frontend depth: you can build backend services, wire up data sources, and produce a polished production-quality interface in the same sprint
• Production experience with AI-powered systems: you have shipped something with streaming output, agent interaction surfaces, human-review workflows, trace inspection interfaces, or similar, and you understand that LLM systems are non-deterministic and must be designed to allow for regular inspection from the start
• React (or equivalent) and modern design systems with the ability to design the interaction AND implement it; you move fluidly between designing in Figma and building in code without the handoff friction that slows most teams down
• Experience with agent observability tooling (Langfuse, LangSmith, Phoenix/Arize, or equivalent) and the ability to design interfaces that make trace data useful to non-engineers
• Data visualization for non-technical audiences; WCAG accessibility standards; JD Power product ecosystem or user base familiarity
• Eval harness design or familiarity with LLM-as-judge patterns understanding what "quality" means for an agentic system informs better inspection interfaces
• Strong product intuition: you ask "what does the user actually need from this agent?" before deciding how to surface it

Company Overview

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