Conversational UX Designer: Flow, Tone & Trust

Wonderful

Milano

On-site

EUR 55,000 - 85,000

Full time

14 days+

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Job summary

Wonderful is seeking a Conversation Experience Designer to shape how people interact with our AI agents—crafting the words, rhythm, and relational dynamics that feel clear and credible.

You’ll design end-to-end dialogue journeys, apply rapport and tone techniques, draft system instructions, and prototype agent responses while testing with real transcripts to improve trust and user follow-through.

Qualifications

  • Experience in UX Writing, Conversation Design, or Prompt Design for LLM-driven applications.
  • Familiarity with NLP frameworks and rapport techniques applied pragmatically.
  • Strong understanding of Large Language Models: context windows, system prompts, tool-calling logic.
  • Ability to transform complex business rules into natural, concise conversational experiences.
  • Portfolio showing conversation flows, prompt strategies, or interactive agent prototypes.

Responsibilities

  • Conversation & Flow Design: design end-to-end dialogue journeys including onboarding, error recovery, and escalation.
  • Trust & Rapport Patterns: apply framing, pacing, and mirroring to reduce hesitation and improve follow-through.
  • Prompt Engineering & Tone of Voice: draft system instructions, guardrails, and context guidelines.
  • Prototyping & Testing: build, simulate, and iterate agent responses across personas.
  • Performance Analysis: review transcripts to flag tone mismatches and unclear phrasing.

Skills

UX Writing & Conversation Design
NLP frameworks familiarity
LLM fundamentals
Natural conversational transformation
Portfolio of dialogues/prototypes

Job description

Wonderful is seeking a Conversation Experience Designer to shape how people interact with our AI agents—crafting the words, rhythm, and relational dynamics that feel clear and credible.

You’ll design end-to-end dialogue journeys, apply rapport and tone techniques, draft system instructions, and prototype agent responses while testing with real transcripts to improve trust and user follow-through.

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