Forward-Deployed AI Solution Architect
QventusRemote, United StatesPosted 24 February 2026
Tech Stack
Job Description
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<p data-pm-slice="1 1 []">On this journey for over 12 years, Qventus is leading the transformation of healthcare. 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.</p>
<p>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. <span style="color: rgb(67, 32, 97);">#LI-JB1</span></p>
<p> </p></div><p><strong>About the Role</strong></p>
<p>We’re looking for an experienced forward-deployed AI Solution Architect to join our AI Platform Partnership team. In this role, you will work as part of a five-person team forward-deployed to a client site. In this role, you’ll apply problem solving ability, creativity, and technical skills to drive AI-powered operational transformations at health systems. You’ll partner cross-functionally with Qventus RD leadership as well as embed with client operational, executive, and IT teams to shape solutions that deliver measurable value.</p>
<p>This is a high-impact role that will influence our AI Operational Assistant platform, strengthen customer outcomes, and shape our company’s growth trajectory. </p>
<p><strong>Key Responsibilities</strong></p>
<ul>
<li>Develop a deep understanding of client context and Qventus capabilities to identify high-leverage opportunities for rapid impact with bespoke AI Operational Assistant workflows</li>
<li>Responsible for the design, execution, and optimization of bespoke AI Operational Assistant use cases at the client</li>
<li>Technical Implementation</li>
<ul>
<li>Leverage LLM-based AI (GPT, Claude, Gemini, LLaMA, etc.) to build advanced conversational systems.</li>
<li>Apply conversation modeling techniques like state machines, decision trees, and graph-based flows.</li>
<li>Use frameworks such as Dialogflow, Rasa, Amazon Lex, Langchain, or similar tools.</li>
<li>Collaborate with backend teams to integrate bots with APIs, CRMs, and enterprise systems.</li>
<li>Enhance bot functionality with custom scripts, API calls, and external system integrations.</li>
</ul>
<li>Optimization, Testing Maintenance</li>
<ul>
<li>Continuously tune and improve intent recognition and response quality using real user data.</li>
<li>Monitor and resolve conversation breakdowns, mismatches, and fallback issues.</li>
<li>Develop and run unit, regression, and A/B tests to ensure conversational performance.</li>
<li>Implement real-time monitoring, analytics, and logging to drive performance insights.</li>
</ul>
<li>Collaboration Documentation</li>
<ul>
<li>Shape client use cases in partnership with the AI Solution Consultant</li>
<li>Collaborate closely with Qventus architects, engineers, and data scientists, as well as client end-users and IT teams to define and refine product requirements</li>
<li>Work closely with software engineers and data scientists to refine LLM integration and behavior.</li>
<li>Document conversation logic, prompt structures, and decision workflows for scalability and maintainability.</li>
</ul>
<li>Mentor and support cross-functional teammates across forward-deployed client team</li>
</ul>
<p><strong>What We’re Looking For</strong></p>
<ul>
<li>5+ y ... (truncated, view full listing at source)
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