 |
Solutions Architect, Conversational AI & Prompt Engineering - Mountain View California
Company: Qventus, Inc Location: Mountain View, California
Posted On: 05/09/2025
Qventus is leading the transformation of healthcare operations. We enable hospitals to focus on what matters most: patient care. Our innovative solutions harness the power of machine learning, generative AI, and behavioral science to deliver exceptional outcomes and empower care teams to anticipate and resolve issues before they arise.Our success in rapid scale across the globe is backed by some of the world's leading investors. At Qventus, you will have the opportunity to work with an exceptional, mission-driven team across the globe, and the ability to directly impact the lives of patients. We're inspired to work with healthcare leaders on our founding vision and unlock world-class medicine through world-class operations.As a Solutions Architect of Conversational AI & Prompt Engineering, you will lead the technical design, development, and optimization of AI-driven conversational agents, as well as contribute to broader prompt engineering across other use cases. This role requires expertise in designing robust conversational flows, implementing intent recognition systems, and structuring chatbot logic into modular and reusable components. The ideal candidate will collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to create and maintain state-of-the-art conversational AI systems, ensuring high-quality, scalable, and intelligent chatbot experiences.Key Responsibilities1. Conversational Logic & Prototypes - Design and implement AI conversational flow logic, considering potential disruptions, multiple conversation turns, and alternate conversation paths to ensure interactions are effective and meet user and business goals.
- Create and manage dialogue state, entity extraction, and intent recognition models.
- Build a scalable and reusable chatbot logic system using a modular design approach.2. Technical Implementation & Development
- Familiarity with conversation modeling techniques, including state machines, decision trees, and graph-based models.
- Experience with LLM-based conversational AI, such as GPT, Claude, Gemini, and LLaMA.
- Ability to use frameworks like Dialogflow, Rasa, Amazon Lex, Langchain, and others to implement conversational AI solutions.
- Integrate chatbots with databases, CRM systems, and enterprise APIs by collaborating with backend developers.
- Enhance chatbot capabilities by writing custom scripts, API calls, and system integrations.
- Develop and optimize intent classification models, slot-filling mechanisms, and context management strategies.3. Testing, Optimization, & Maintenance
- Improve chatbot intent recognition and response generation through continuous training and tuning.
- Optimize accuracy by analyzing user interactions, intent mismatches, and conversational breakdowns.
- Develop and execute unit tests, regression tests, and A/B tests to improve chatbot performance.
- Implement real-time monitoring, logging, and analytics to track performance and user satisfaction.4. Collaboration & Documentation
- Collaborate with product teams to ensure chatbot functionalities align with business goals.
- Work with software developers and data scientists to refine language models.
- Document conversational logic, decision trees, and workflow diagrams for scalability and maintenance.It's a plus if you have
|
 |