Conversational Design 

• Design end-to-end conversational experiences including dialog flows, scripts, intents, prompts, and responses. 

• Craft natural, human-like conversational language aligned with brand tone. 

• Develop decision trees, multi-turn flows, error handling, contextual prompts, and fallback logic. 

• Optimize conversations for clarity, efficiency, and user satisfaction across chat and voice interfaces. 

User Research & Testing 

• Conduct user interviews, usability tests, and A/B experiments to validate conversational designs. 

• Analyze transcripts, user behavior, and interaction data to identify pain points and refine flows. 

• Translate insights into design improvements and new conversation opportunities. 

Collaboration & Documentation 

• Partner with Product, Engineering, and AI/NLP teams to ensure designs are feasible and technically aligned. 

• Work with data scientists and linguists to refine intent models and training data. 

• Create and maintain conversation design documentation, user journeys, style guides, and content standards. 

Optimization & Continuous Improvement 

• Evaluate conversational performance using metrics such as CSAT, containment rates, NLU accuracy, and task completion. 

• Iterate based on user feedback, analytics, and business goals. 

• Stay updated on conversation design trends, LLM best practices, and emerging AI experience patterns. 

Qualifications 

Required 

• 3–5 years of experience in UX writing, conversation design, content design, or interaction design. 

• Hands-on experience creating conversational flows for chatbots, virtual assistants, or voice apps (e.g., Alexa, Google Assistant). 

• Strong writing skills with an ability to craft clear, concise, and natural-sounding dialogue. 

• Experience with tools such as Figma, Miro, Dialogflow, Rasa, Lex, Voiceflow, Botmock, or similar platforms. 

• Understanding of NLP/NLU concepts, intents/entities, and user behavior. 

• Ability to work collaboratively with cross-functional teams in an Agile environment. 

Preferred 

• Background in linguistics, psychology, UX research, cognitive science, or communication. 

• Experience designing for large language model (LLM)–based assistants. 

• Knowledge of accessibility standards and inclusive design principles. 

• Experience with analytics tools for conversation performance tracking