Do you have a strong work ethic and the desire to join an organization that invests in its people through cross-training and development? ClarkDietrich fosters a work-life balance and offers competitive compensation and benefits. Join the ClarkDietrich team by applying to the Conversational AI Specialist position at our West Chester, OH location.
Job Summary
The Conversational AI Specialist will help turn Customer Experience AI strategy into practical execution across customer and internal service use cases. This role is responsible for improving chatbot and conversational AI experiences, structuring knowledge and content for high-quality AI responses, and enabling teams to apply AI effectively in day-to-day work.
This is a hands-on, execution-focused role for someone who combines strong business-side AI fluency with experience in B2B customer service, EDI customer service, support operations, onboarding, customer success, or similar customer-facing environments. The role does not require software development expertise, but it does require comfort configuring and improving no-code or low-code AI and chatbot solutions, partnering with Digital/IT teams, and bringing structure to ambiguous opportunities.
This role will report to the Digital Program Manager -- CX and serve as the CX-side lead for conversational experience design, intents, knowledge, testing, and optimization across existing platforms and vendor relationships.
Key Responsibilities
Conversational AI Execution and Optimization
Own the CX-side execution of chatbot and conversational AI experiences across customer and internal service use cases.
Design, test, refine, and optimize conversational flows, intents, prompts, response patterns, and escalation paths.
Identify and prioritize opportunities to reduce repetitive service demand through AI-enabled self-service.
Monitor chatbot and conversational AI performance and recommend improvements to increase containment, answer quality, and user satisfaction.
Support launch planning and rollout of new conversational AI use cases within existing tools and vendor environments.
Work across existing platforms and tools to improve conversational experiences, service workflows, and team adoption, with particular emphasis on business use cases rather than tool ownership.
Knowledge and Content Structuring
Organize, improve, and maintain knowledge sources, content structures, FAQs, and business rules that support accurate AI responses.
Partner with subject matter experts across CX, sales, onboarding, and related functions to capture and structure knowledge for AI use.
Help define content standards and governance practices that improve retrieval quality, consistency, and usability.
Translate complex B2B service and operational processes into AI-ready knowledge and conversation logic.
Continuously identify content gaps, inconsistent documentation, and unclear business rules that affect AI performance.
Team Enablement and Adoption
Train and coach CX and customer-facing teams on practical AI usage in daily workflows.
Help teams adopt effective prompting, workflow habits, and quality standards across approved AI tools.
Bring structure and discipline to emerging AI opportunities by helping teams move from ideas to practical business use cases.
Create playbooks, guidance, and lightweight documentation that improve repeatability and adoption.
Support internal change management by helping non-technical teammates build confidence and skill with AI-enabled workflows.
Cross-Functional Collaboration
Partner closely with CX, sales, onboarding, and Digital/IT stakeholders to improve conversational experiences and align business requirements.
Serve as the CX lead for business-side chatbot and conversational AI requirements, knowledge design, and user experience decisions.
Work within current platform and vendor relationships, helping evaluate fit for use cases and justify additional tools only when clearly needed.
Support selected customer meetings, trade shows, and external conversations when conversational AI capabilities or customer workflow needs are relevant.
Help bridge customer-facing business needs with technical teams without owning deep technical integration architecture.
Year One Success Measures
Success in this role will be measured primarily by launching and improving AI/chatbot experiences that measurably reduce live-service demand.
Additional success will be measured by improving AI answer quality through stronger knowledge and content structure, increasing practical AI adoption across CX and adjacent customer-facing teams, and creating more consistent, scalable conversational experiences across existing platforms.