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NEXTMOVEFDE careers · United States

AI Tooling Engineer

No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.

About Qventus

AI-powered decision and automation platform helping hospitals optimize operations, scheduling, and patient flow through machine learning and behavioral science.

Series D · 200–500 people

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Internal deployment & tooling · Evidence for this classification:

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. 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. #LI-MB1 About the Role We're hiring Engineers dedicated to building AI-powered tools that change how work gets done inside the company.
More from the job description

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. 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. #LI-MB1 About the Role We're hiring Engineers dedicated to building AI-powered tools that change how work gets done inside the company. You'll embed with teams across operations, customer success, and finance, find the work that's slow and manual, and ship AI agents and automations that actually get adopted. This is a build-fast, talk-to-humans, own-the-problem role - not a research role and not a pure-infrastructure role. You'll define what "internal AI" looks like here from scratch. Who this is for You're energized by ambiguity and ownership. You'd rather ship a rough tool this week, watch someone use it, and improve it than [... source excerpt omitted ...] al teammate, understanding their actual workflow, and turning it into something that saves them hours. You're comfortable being the only person who owns a problem end to end. Who you will work with You'll partner closely with the CEO and founders on identifying the highest-leverage operational problems to solve and shaping where internal AI goes next. This is a rare amount of executive access to an engineering role. You’ll work alongside functional leaders across the business to understand their priorities, surface opportunities , and align on what to build. Your work will be visible and leadership level from day one. Operations, Customer Success, Finance, People/Talent Acqui [... source excerpt omitted ...] ion, Engineering, IT and Data teams, these are your internal customers and collaborators. You'll embed with them, and learn their workflows and ship tools they actually use. What you'll actually build Examples of the kind of work waiting for you: An agent that drafts customer success replies from our knowledge base and ticket history A Slack-based workflow that routes and pre-fills finance approvals An internal eval harness so we can trust the LLM features we ship A tool that lets the ops team query [internal system] in plain language You won't do all of these at once — you'll pick the highest-impact one, ship it, and move to the next. What we're looking for 1–3 years

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