Principal Content Designer, AI Experiences

Autodesk Autodesk · Enterprise · Toronto, ON +4 · Remote

This Principal Content Designer role focuses on defining and designing the language, interaction, and intelligence of AI experiences within Autodesk's product design and manufacturing tools. The role involves hands-on content design for AI initiatives and agent experiences, creating scalable language and explanation frameworks to ensure clear, trustworthy AI communication. It requires close collaboration with AI, design, product, and engineering teams to translate AI platform guidance into practical in-product patterns and mentor other designers.

What you'd actually do

  1. Lead hands‑on content design for priority AI initiatives and agent experiences, from early concept through launch, including conversational flows, embedded guidance, and system feedback
  2. Define and evolve scalable language and explanation frameworks that guide how AI communicates intent, actions, uncertainty, and outcomes across agents
  3. Design clear in‑product explanations, prompts, and feedback loops that make AI behavior understandable and actionable for customers in real workflows
  4. Partner closely with AI, experience design, product, and engineering teams to ensure language, interaction, and system behavior form a cohesive, trustworthy experience
  5. Translate AI platform guidance into practical, shippable content patterns that teams can apply consistently in live products

Skills

Required

  • Content design for AI experiences
  • Designing conversational, embedded, or agentic systems
  • Developing language and explanation patterns for AI
  • Collaboration with AI, UX, product, and engineering teams
  • Systems thinking beyond microcopy
  • Communication and mentoring skills

Nice to have

  • Experience in product design and manufacturing software

What the JD emphasized

  • Hands-on experience developing AI-driven product experiences, including conversational, embedded, or agentic systems
  • Strong ability to design language and explanation patterns that make system behavior understandable, predictable, and trustworthy for users
  • Demonstrated success partnering with UX, product, engineering, and AI teams, influencing decisions through collaboration rather than ownership
  • Comfort operating in ambiguity, shaping new patterns and practices as AI capabilities evolve

Other signals

  • designing AI experiences
  • AI initiatives and agent experiences
  • language and explanation frameworks
  • trustworthy AI at scale
  • AI explains actions, requests input, and provides feedback