AI Experience Engineer

AI Experience Engineer at JD Power is a full-stack role responsible for the complete human-facing layer of AI-powered systems, from data models to backend services to polished production interfaces. As part of the Innovation Crew, you will design and build interactions that make agentic AI capabilities legible, trustworthy, and useful to engineers, analysts, and business stakeholders. You will implement an observable, traceable system that allows humans to assess processes when needed and to course-correct without being in the critical path of every step. You will audit and contribute to the design system, ship agent interaction components, and develop observability interfaces enabling the team to review agent traces without engineering intervention.

Responsibilities

• Own the full-stack design and engineering quality for all Innovation Crew pilots and prototypes, delivering backend services, API integrations, and polished production-quality interfaces that are accessible and legible to non-technical audiences.
• Design human-on-the-loop interaction patterns for agentic systems, building interfaces for engineers and reviewers to inspect agent traces, audit reasoning outputs, adjust parameters, and surface anomalies while keeping humans in control without bottlenecks.
• Build and maintain a shared design system and component library for Innovation Crew outputs, including AI-specific components such as streaming outputs, agent status indicators, trace inspection views, confidence surfaces, and human-review interfaces for production use.
• Define UX standards and interaction vocabulary for the AI Assistants and Copilots capability pillar, including contextual AI assistance interfaces, real-time knowledge retrieval surfaces, AI-generated content displays, and role-specific intelligence dashboards.
• Conduct lightweight user research and usability testing with internal stakeholders and business partners, incorporating user feedback early to shape what gets built; collaborate with the Principal AI Engineer to design evaluation interfaces and observability dashboards that make model behavior readable for human reviewers.
• Champion WCAG accessibility standards and performance engineering across deliverables; apply brand guidelines to externally shown outputs; contribute UX and frontend evaluations to the Emerging Technology Radar and propose Architecture Decision Records for AI interaction patterns the team adopts.

Qualifications

• Full-stack engineering with frontend depth, capable of building backend services, wiring data sources, and delivering production-quality interfaces in the same sprint.

• Production experience with AI-powered systems, including streaming outputs, agent interaction surfaces, human-review workflows, and trace inspection interfaces; understanding that LLM systems are non-deterministic and require observable design from the start.

• React (or equivalent) and modern design systems experience, with the ability to design and implement interfaces, switching smoothly between design in Figma and implementation in code.

• Valued Experience

• Experience with agent observability tooling (e.g., Langfuse, LangSmith, Phoenix/Arize) and designing interfaces that make trace data accessible to non-engineers.

• Data visualization for non-technical audiences; WCAG accessibility standards; familiarity with JD Power product ecosystem or user base.

• Eval harness design or familiarity with LLM-as-judge patterns to inform better inspection interfaces.

• Strong product intuition: focus on user needs and how best to surface agent capabilities.

• Hiring Manager’s Perspective

• The ideal candidate understands that the interface is essential to building trust, not decoration. You design systems where humans can see what happened, understand why, and intervene when needed without being in every decision loop. The work will be shown to executives and potentially external clients, and your name will be associated with it.

Compensation

This position offers a starting salary range of 130,000 to 160,000 USD or 115,000 to 130,000 CAD per year, with pay determined by skills, education, qualifications, experience, performance, business needs, and location.