Conversation Designer

As part of the Conversation Design team, you'll help shape what great AI conversation experiences look and sound like — across channels and languages, for enterprise customers around the world. You'll work directly with customers and internal teams to improve agent quality — especially in voice, one of our fastest growing channels — and build the systems and resources that allow us to scale your expertise.

This work spans research, design, enablement, and product strategy. You might:

Advise customers and internal teams on conversation design and voice selection

Evaluate and iterate on voice quality across providers, languages, and use cases

Build playbooks, rubrics, and evaluation frameworks that scale best practices across the team

Partner with Engineering and Product to translate field insights into platform improvements

Your insights will shape how Decagon deploys AI in mission-critical contexts and how we build toward the next generation of intelligent systems.

In this role, you will

Design and optimize enterprise-grade AI conversation experiences across chat, voice, SMS, and email channels

Serve as a trusted advisor to customers and internal stakeholders on conversation design best practices

Evaluate voice quality and interaction patterns to maintain a high bar for naturalness and appropriateness

Build repeatable frameworks for assessing conversation and voice performance

Enable our Customer team to apply strong design judgment independently

Partner crossfunctionally with Engineering and Product to investigate quality gaps and drive improvements through clear recommendations

Share learnings and create documentation on best practices to improve consistency and raise the quality bar across deployments

Your background looks something like this

5+ years of relevant experience (e.g., voice experience design, conversation designer, product manager, applied linguistics, etc.)

Hands-on experience with voice — conversational AI, speech synthesis, or audio production

Experience migrating NLU systems to LLM and understanding key use cases for RAG functionality improvements

Experience building evaluation frameworks, rubrics, or QA processes

Strong communicator across technical and business contexts

Comfortable working close to the product in a fast-moving environment

Even better if you have

Native or professional fluency in Spanish and/or familiarity with other languages

Experience with TTS providers or speech synthesis tools

Hands-on experience with frontier AI tools and deployment in enterprise or high-impact settings

Compensation

$180K - $220K + Offers Equity