AI Experience Engineer

Accountabilities:

• • Own full-stack delivery: Take Innovation Crew concepts from initial brief or wireframe through backend services, API integrations, data connections, and polished production-quality interfaces.
  • Build AI interaction experiences: Design and implement intuitive interfaces for AI-powered systems, ensuring outputs, interactions, and workflows are understandable to both technical and non-technical users.
  • Develop human-on-the-loop experiences: Create interfaces that allow users to inspect agent traces, review outputs, adjust parameters, identify anomalies, and intervene when necessary without requiring human approval at every stage.
  • Build a shared design system: Develop and maintain reusable components for AI experiences, including streaming outputs, agent status indicators, progress views, trace inspection, confidence displays, and human-review workflows.
  • Define AI interaction standards: Establish reusable UX patterns for contextual AI assistance, real-time knowledge retrieval, AI-generated content, intelligent dashboards, and agent-based experiences.
  • Improve usability through research: Conduct lightweight user research and usability testing with internal stakeholders and business partners, incorporating feedback early into product and experience decisions.
  • Enable AI observability: Collaborate with AI engineering teams to create evaluation interfaces and observability dashboards that make model behavior and agent traces understandable to human reviewers.
  • Champion accessibility and performance: Apply WCAG accessibility standards and performance engineering practices across deliverables while maintaining consistency with applicable brand and product guidelines.
  • Evaluate emerging technologies: Contribute to frontend and UX technology evaluations and help establish architectural recommendations and reusable patterns for AI interaction.
  • Support knowledge sharing: Document successful interaction patterns and reusable components so they can be adopted by broader engineering and product teams.
  • Deliver executive-ready experiences: Ensure prototypes and solutions presented to leadership or external stakeholders are visually consistent, accessible, compelling, and immediately understandable.

  Requirements

  • Full-stack engineering experience: Demonstrated ability to build backend services, integrate data sources and APIs, and deliver polished frontend experiences within the same development cycle.
  • AI product experience: Production experience with AI-powered systems, particularly streaming interfaces, agent interactions, human-review workflows, trace inspection, or similar AI experience patterns.
  • Frontend expertise: Strong experience with React or an equivalent modern frontend framework, combined with the ability to design and implement modern design systems.
  • Design-to-code capability: Comfortable moving between tools such as Figma and production code, with strong UX instincts and the ability to independently translate interaction concepts into working experiences.
  • AI systems understanding: Strong understanding of the non-deterministic nature of LLM-powered systems and the importance of designing for observability, inspection, evaluation, and human intervention.
  • Agent observability: Experience with tools such as Langfuse, LangSmith, Phoenix, Arize, or equivalent platforms is highly valued.
  • Data visualization: Ability to present complex data and system information clearly to non-technical audiences.
  • Accessibility: Knowledge of WCAG standards and experience applying accessibility principles to digital products.
  • AI evaluation: Familiarity with evaluation harnesses, LLM-as-judge approaches, or other methods for assessing the quality and reliability of agentic systems is a plus.
  • Product thinking: Strong product intuition and the ability to start with user needs and desired outcomes when deciding how AI capabilities should be surfaced.
  • Communication and collaboration: Strong ability to work across engineering, design, product, and business teams and communicate complex technical concepts clearly.
  • Trust and quality mindset: A strong understanding that AI interfaces must make system behavior understandable and trustworthy rather than simply presenting successful demonstrations.

  Benefits

  • Competitive compensation: Starting salary range of $130,000–$160,000 USD or $115,000–$130,000 CAD per year, depending on skills, experience, qualifications, performance, business needs, and location.
  • Remote flexibility: Fully remote opportunity available to professionals based in Canada.
  • High-impact AI work: Build production-quality experiences for emerging AI assistants, copilots, and agentic systems.
  • Technical ownership: Significant opportunity to influence AI interaction patterns, observability standards, design systems, and engineering practices.
  • Innovation-focused environment: Work on emerging technologies where experimentation, practical problem-solving, and continuous improvement are encouraged.
  • Cross-functional collaboration: Partner with engineering, AI, product, and business stakeholders on highly visible initiatives.
  • Inclusive workplace: Join an environment committed to diversity, equal opportunity, collaboration, and respect.
  • Accessibility support: Recruitment accommodations are available for qualified candidates who require them.