Senior Conversation Designer | Agentic Commerce

Role Overview:

We are seeking a Conversation Designer who understands how agentic commerce transforms interactions from static scripts into adaptive, AI-mediated exchanges. This role blends conversational design, experience design, and structured content strategy to craft intelligent dialogue systems that are brand-forward, agent-compatible, and continuously optimized through signals, structure, and feedback loops. 

You will design AI-native conversational ecosystems that enable brands to show up effectively in environments where intelligent agents shape discovery, guide decision-making, negotiate value, and increasingly act on behalf of customers. 

Job Responsibilities 

Conversational Vision for Agentic Journeys. Defining how brands behave across adaptive, agent-mediated interactions, including: 

• Mapping dynamic conversational journeys that evolve based on agent inference, contextual signals, and user intent. 

• Designing structured dialogue architectures that support both human-agent and agent-to-agent interactions. 

• Ensuring conversational systems include decision support frameworks that intelligent agents can parse, reference, and optimize. 

• Translating brand voice into machine-operable behavioral guidelines for AI-driven exchanges. 

Dialogue Architecture and Interaction Design. Shaping how customers and intelligent agents engage through adaptive interfaces, including: 

• Crafting modular conversational flows that balance brand personality with clarity, intent recognition, and agent-friendly structure. 

• Designing slot-filling patterns, prompt scaffolds, fallback states, and escalation paths. 

• Creating reusable conversation components that support personalization and optimization at scale. 

• Designing repair strategies and trust-building mechanisms when AI confidence is low or ambiguity is high. 

Structured Content and Intent Modeling for GEO/AEO. Building dialogue systems that are strategically structured for LLM reasoning, retrieval, and generative reinterpretation, including: 

• Developing taxonomies of intents, entities, and conversational variables. 

• Writing modular, semantically tagged content that improves agent comprehension and retrieval accuracy. 

• Designing conversational patterns that surface high-quality signals for GEO/AEO optimization. 

• Collaborating with content strategists and optimization teams to ensure dialogue systems improve findability, answer quality, and agent preference over time. 

Optimization-Centered Conversational Strategy. Embedding experimentation and continuous improvement into dialogue systems, including: 

• Partnering with GEO practitioners and data teams to translate model insights into conversational refinements. 

• Designing experiments that test tone, framing, response length, structured prompts, and negotiation patterns. 

• Monitoring interaction performance and identifying opportunities to improve clarity, trust, and conversion outcomes. 

• Ensuring conversational systems evolve responsibly through structured testing and signal analysis. 

Trust, Transparency and Ethical Dialogue Design. Designing conversations that build long-term trust in autonomous and semi-autonomous systems, including: 

• Crafting explainability patterns that clarify agent reasoning and decision pathways. 

• Designing consent and confirmation flows for agent-initiated transactions. 

• Avoiding dark patterns and ensuring ethical behavioral design principles guide persuasive interactions. 

• Defining escalation models where human intervention enhances safety and confidence.