Senior Conversation Designer | Agentic Commerce

Accenture•Kirkland, WA

1d•$87,400 - $266,300

About The Position

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.

Requirements

5+ years of experience designing conversational systems for chat, voice, multimodal, or AI-assisted commerce environments; with strong understanding of intent modeling, conversational taxonomies, and structured content systems.

Nice To Haves

Bachelor’s degree in Design, Human-Computer Interaction, Linguistics, Communications, or a related field.
Industry experience in Retail and Consumer Goods & Services.
Exceptional writing skills with demonstrated ability to translate brand voice into structured dialogue systems.
Experience collaborating with product, engineering, and data teams on AI-enabled experiences.
Familiarity with Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) principles.
Proficient in developing conversational prototypes, documentation, and training materials.
A passion for innovation and a commitment to helping clients adopt AI-driven interaction models responsibly.

Responsibilities

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.
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.
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.
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.
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.