We are a team of technologists, software engineers, doctors, nurses, and lean healthcare experts with on-the-ground experience solving operational challenges in clinical environments. Qventus helps hospitals like Stanford/Mayo Clinic/Emory/New York Presbyterian reduce wait time for patients, prevent patient falls, and generally helps hospitals deliver a better and safer experience for patients, resulting in reduced injuries, loss of life, and financial waste.

We're making a big difference. Qventus has meaningfully affected patient experiences and outcomes for almost 4 million patients across the united states. Our platform works with hospital data to predict negative outcomes for patients and associated potentially disastrous situations that are likely to occur, then applies our system of action to reach the right doctors and nurses, at the right time, telling them where to go to stop these events before they happen. Think Minority Report applied to hospitals.

Our founding team has done this before. Two of our three founders worked in consulting for over a decade solving efficiency problems in hospitals. They know hospitals, where they've been, where they want to go, and how to work within them to drive the necessary mind shift and change management we need to drive this new wave of technology.

Our team is top notch! We have the fortune of having amazing engineerings and data scientists from top schools (Stanford, MIT, Cal, etc.) applying the latest in artificial intelligence and machine learning to create products that help healthcare organizations around the world and their people adapt in the moment and make the right decisions from the most complex data. Furthermore, we employ several practicing clinicians (practicing surgeons, doctors, nurses) in the company to help us understand the hospital environment. We take what we do very seriously.

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.

Engineering is comprised of several teams: - Web Apps: Responsible for our web platform and associated services. - Mobile: Responsible for our mobile products (iOS and Android). - Data Platform: Responsible for ETL, data processing and platform, managing data lifecyle from customer ingest to persistence, serving data to data science and web apps groups. - Data Science: Responsible for our ML development. - DevOps: Infrastructure and associated infrastructure services, working with teams to build and maintain CI/CD pipelines. - QA: Responsible for quality definition, automation, QA infrastructure, driving quality process from development through release. Functional QA is largely outsourced, we prefer to have QA team focused more on the engineering required to scale a large QA org.

Some of the challenges we are facing:

1. Using AI/ML- We use predictive analysis to help doctors and nurses make proactive operational decisions so they can focus on patient care

2. Data scaling- We are starting to get significantly larger volumes of data, which is also increasingly becoming more and more clinical (lab results, etc) in nature.

3)Data sensitivity- Because this data is more clinical, it is more sensitive and requires a higher bar on how we set up and monitor our systems.

4)Data Ingestion- Getting data out of hospitals is not an easy task. We have to figure out more scalable solutions to help us grow quickly. This is an industry wide problem and we are looking to do it better than just about anyone else.

5)Product growth- Expansion in more areas of the hospital means we have more to learn and an opportunity to expand our product to achieve more outcomes.