• Develop a deep understanding of client context and Qventus capabilities to identify high-leverage opportunities for rapid impact with bespoke AI Operational Assistant workflows • Responsible for the design, execution, and optimization of bespoke AI Operational Assistant use cases at the client • Technical Implementation • Leverage LLM-based AI (GPT, Claude, Gemini, LLaMA, etc.) to build advanced conversational systems. • Apply conversation modeling techniques like state machines, decision trees, and graph-based flows. • Use frameworks such as Dialogflow, Rasa, Amazon Lex, Langchain, or similar tools. • Collaborate with backend teams to integrate bots with APIs, CRMs, and enterprise systems. • Enhance bot functionality with custom scripts, API calls, and external system integrations. • Optimization, Testing & Maintenance • Continuously tune and improve intent recognition and response quality using real user data. • Monitor and resolve conversation breakdowns, mismatches, and fallback issues. • Develop and run unit, regression, and A/B tests to ensure conversational performance. • Implement real-time monitoring, analytics, and logging to drive performance insights. • Collaboration & Documentation • Shape client use cases in partnership with the AI Solution Consultant • Collaborate closely with Qventus architects, engineers, and data scientists, as well as client end-users and IT teams to define and refine product requirements • Work closely with software engineers and data scientists to refine LLM integration and behavior. • Document conversation logic, prompt structures, and decision workflows for scalability and maintainability. • Mentor and support cross-functional teammates across forward-deployed client team