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Solutions Architect, Conversational AI & Prompt Engineering

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 Responsibilities

1. 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

  • Experience with conversational AI voice systems

  • Strong understanding of vector databases, embeddings, and retrieval-based chatbot models.

  • Hands-on experience with embeddings, vector search, and RAG (Retrieval Augmented Generation).

  • Understanding of knowledge graphs and their application in chatbot workflows.

  • Experience using machine learning techniques for intent recognition and dialogue management.

  • Previous work with chatbot solutions in healthcare.

The salary range for this role is $120,000 to $200,000. Qventus salary bands represent market data across different geographies. We consider several factors when determining compensation, including location, skills and qualifications, and prior relevant experience. Salary is just one component of Qventus’ total package. Some of our key benefits and perks* include but are not limited to: Open Paid Time Off, paid parental leave, professional development, wellness, and technology stipends, generous employee referral bonus, and employee stock option awards.

We believe that diversity, equity, inclusion, and belonging are fundamental to improving healthcare and society, and that’s why we’re building a company that leads the way. We hold ourselves accountable to using fair hiring processes that mitigate the negative impacts of unconscious bias. We also work to ensure that people from underrepresented groups play meaningful roles on both sides of the interview table. We are an equal opportunity employer and give all qualified applicants consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.

Candidate information will be treated in accordance with our candidate privacy notice which can be found here: https://qventus.com/ccpa-privacy-notice/

Employment is contingent upon the satisfactory completion of our pre-employment background investigation and drug test.

*Benefits and perks are subject to plan documents and may change at the company's discretion.

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What You Should Know About Solutions Architect, Conversational AI & Prompt Engineering, Qventus

At Qventus, we are revolutionizing healthcare operations, and we are excited to invite a talented Solutions Architect specializing in Conversational AI & Prompt Engineering to join our Mountain View team. In this pivotal role, you will be at the forefront of crafting intelligent conversational agents that enhance patient interactions with healthcare systems. Your expertise will empower care teams to navigate challenges seamlessly, utilizing machine learning and cutting-edge AI technologies. You’ll design robust conversational flows, implement effective intent recognition systems, and work closely with a dynamic team of data scientists and software engineers. Your innovative mindset will contribute to building scalable, reusable chatbot systems, while also ensuring that they meet both user and business needs effectively. As you lead technical design and development, you’ll collaborate with cross-functional teams to maintain high-quality conversational experiences. We look for someone who is deeply familiar with AI-driven conversational models like GPT and Rasa, able to integrate complex systems while optimizing for performance. If you are ready to make a meaningful impact on patient care through transformative technology, Qventus is the perfect place to bring your passion to life.

Frequently Asked Questions (FAQs) for Solutions Architect, Conversational AI & Prompt Engineering Role at Qventus
What are the main responsibilities of a Solutions Architect at Qventus?

As a Solutions Architect at Qventus, your primary responsibilities include designing AI conversational flow logic, implementing intent recognition systems, and ensuring high-quality chatbot experiences. You will be developing modular chatbot logic while collaborating with software engineers and data scientists to maintain scalable systems.

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What qualifications do I need to apply for the Solutions Architect position at Qventus?

To apply for the Solutions Architect position at Qventus, candidates should have a strong background in AI and conversational systems, experience with frameworks like Dialogflow and Rasa, as well as familiarity with LLM-based conversational AI techniques. Additionally, a solid understanding of conversation modeling and chatbot logic is essential.

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What is the salary range for the Solutions Architect role at Qventus?

The salary range for the Solutions Architect role at Qventus is between $120,000 and $200,000. Compensation is based on various factors, including location, skills, qualifications, and relevant experience, and is part of a comprehensive benefits package we offer.

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How does Qventus ensure diversity and inclusion in hiring for the Solutions Architect position?

Qventus is committed to diversity, equity, inclusion, and belonging. We emphasize fair hiring processes that mitigate unconscious bias and actively seek candidates from underrepresented groups to ensure meaningful roles within our teams.

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What benefits can I expect as a Solutions Architect at Qventus?

As a Solutions Architect at Qventus, you can expect a robust benefits package that includes Open Paid Time Off, paid parental leave, wellness and technology stipends, along with professional development opportunities and stock option awards.

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Common Interview Questions for Solutions Architect, Conversational AI & Prompt Engineering
Can you explain how you approach designing conversational flows for AI systems?

In designing conversational flows, I start by understanding user goals and potential disruptions. My approach includes mapping out dialogue states, using decision trees or state machines, and considering multiple conversation pathways to ensure seamless interactions.

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What experience do you have with integrating AI chatbots with existing enterprise systems?

I have integrated AI chatbots with various enterprise systems by collaborating with backend developers to create API interactions. My experience involves ensuring smooth data flow between the chatbot, CRM systems, and databases while maintaining an intuitive conversation for users.

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How do you optimize and test chatbot performance?

I utilize a systematic approach to optimize chatbot performance, which includes conducting user interaction analysis, regression tests, and A/B testing. Continuous training of intent recognition models and real-time monitoring are also critical aspects of my testing strategy.

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What frameworks have you used for building conversational AI solutions?

I have experience working with frameworks like Rasa, Dialogflow, and Amazon Lex. Each framework offers unique capabilities, and I select the one that best aligns with the project requirements to deliver scalable and reliable conversational experiences.

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Describe your experience working with natural language processing (NLP) techniques?

My experience with NLP includes developing intent recognition models, entity extraction processes, and slot-filling strategies that streamline user interactions. I stay updated on the latest NLP techniques to implement improvements in chatbot functionality.

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How do you ensure that chatbot responses meet business objectives?

I ensure that chatbot responses align with business objectives by collaborating closely with product teams during the design phase. Regular updates and reviews of user feedback also help me refine responses to enhance both user satisfaction and business alignment.

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What challenges have you faced in conversational AI projects and how did you overcome them?

One challenging project involved high variability in user input. To overcome this, I implemented advanced intent recognition algorithms and continuously trained the model with new data, which ultimately improved the chatbot's accuracy and user experience.

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How familiar are you with machine learning techniques in the context of chatbot development?

I am quite familiar with machine learning techniques, particularly for intent recognition and dialogue management. I incorporate ML algorithms to enhance the true understanding of user inputs and to optimize the overall conversational flow in AI applications.

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What strategies do you employ when optimizing for accuracy in conversational AI?

To optimize for accuracy, I analyze user interactions, investigate intent mismatches, and utilize user feedback to adjust the system. Continuous retraining of models based on real-world data is a crucial part of my strategy.

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Can you discuss your approach to documentation within conversational AI projects?

My approach to documentation involves maintaining clear, detailed records of conversational logic, decision trees, and workflow diagrams. This facilitates scalability and ensures that both technical and non-technical team members can follow the development process effectively.

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Qventus’ mission is to simplify how healthcare operates with the first “System of Action” that brings together data, technology and people to make it possible for hospitals to run their operations efficiently, in real time and at scale. It’s the o...

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March 24, 2025

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