AI Experience Engineer

🏢 J.D. Power · all J.D. Power jobs
📍 Canada
💰 USD 130,000 - 160,000 / annual
📅 Posted 2026-08-14 · via Himalayas
🏷 AI-Experience-Engineer,Full-Stack-Engineer,UX-Engineer,AI-ML-Product-Engineer,Frontend-Engineer,Customer-Experience-AI-Engineer,AI-Interaction-Engineer,AI-Experience-Designer,AI-Engineer,AI-Product-Engineer,Digital-Experience-Engineer,AI-Experience-Design
Apply on original site ↗

Job Description:

Title:   AI Experience Engineer (P4)

Location:  Remote – USA, Canada, Europe or Australia

Reports to: Sr. Director, AI & Innovation

Vacancy :New - Internal Posting

The Role:   

AI Experience Engineer is a full-stack role. You are not a frontend engineer with design instincts and you are not a UX designer who codes. You are an engineer who owns the complete human-facing layer of AI-powered systems from data model through backend service through polished, production-quality interface. On the Innovation Crew, that means designing and building the interactions that make agentic AI capabilities legible, trustworthy, and useful to engineers, analysts, and business stakeholders. Your observability standard is not a human approval gate on every agent output. It is an inspectable, traceable system where humans can assess the process as needed, surface what matters when it matters, and course-correct without being in the critical path of every step. In your first 30 days, you will have audited the team's current design system and shipped your first agent interaction component. By day 60, you will have a working observability interface that lets the team review agent traces without engineering intervention. By day 90, the design system foundations are documented and available to Launch Lab for production consumption.

How we Build Agents:

The Innovation Crew is actively forming its own AI agent workforce to accelerate delivery. As AI Experience Engineer, your contribution to that workforce is the observability and interaction layer: the interfaces that let engineers review agent traces, inspect outputs, and course-correct when needed without becoming bottlenecks in every agent cycle. You bring the "human on the loop" standard to life: observable systems where a person can assess what happened and intervene when it matters, rather than approve every step. When a pattern for AI interaction or agent observability works, you document it as a reusable component and share it with the engineering organization.

The Impact You Will Have in This Role:  

The interfaces you build are often the first thing a business executive or engineering director sees when the Innovation Crew presents a new capability. Your work determines whether a technically sophisticated system lands as a compelling, trustworthy vision or a confusing demo. Beyond individual demos, the interaction patterns and component library you define will shape how JD Power's AI Assistants and Copilots capability pillar is experienced across the organization. The observability interfaces you design for the team's agent workforce will become the model for how humans stay informed about and in control of autonomous systems at JD Power.

What You’ll Be Doing in This Role:

-
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 an

← All remote jobs