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AI Experience Engineer

J.D. Power•Canada•🌍 Remote
Full-timeMid Level
$130K - $160K
per year
👁️ 0 views•📝 0 applications•Posted 10/13/2026•Expires 12/12/2026
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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

Required Skills

full-stack developmentAI-powered systemsdata modelingbackend servicesproduction-quality interfacedesign systemsobservabilityagent interaction componentstraceable systemshuman-centered designAI interaction patternsreusable componentsengineering intervention
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