
Job Overview
Location
Remote (United States)
Job Type
Full-time
Category
HR & Recruiting
Date Posted
April 6, 2026
Full Job Description
đź“‹ Description
- • As an Implementation Lead for Clinical Documentation at SmarterDx, you will drive the operational and technical deployment of SmarterNotes, an EHR-embedded clinical documentation solution that helps hospitals recover missed revenue, improve quality scores, and appeal denials by connecting clinical context with revenue intelligence.
- • You will lead implementations from contract signature through go-live and early adoption, defining milestones, managing scope and risks, coordinating with integration teams for clean data ingestion, facilitating workflow discovery sessions, providing at-the-elbow training and support, and contributing to scalable implementation standards while capturing client feedback to inform the product roadmap.
- • SmarterDx, founded by physicians in 2020 and part of Smarter Technologies, builds clinical AI that transforms how hospitals translate care into payment, operating with a remote-first culture and a mission to optimize the healthcare system for everyone through high-impact, low-bureaucracy innovation.
- • In this role, you will deepen your expertise in EpicCare Inpatient Clinical Documentation workflows, gain experience leading complex healthcare SaaS implementations, develop scalable implementation frameworks, and strengthen your ability to engage clinical, operational, and technical stakeholders to drive adoption of physician-facing tools that improve documentation quality and downstream outcomes.
Skills & Technologies
About SmarterDx, Inc.
SmarterDx provides AI-powered clinical documentation integrity software that retrospectively reviews inpatient EHR data to identify missed diagnoses, quantify clinical quality gaps, and optimize revenue integrity for hospitals and health systems. Its machine-learning models surface overlooked conditions, prioritize cases for review, and feed corrected coding back to billing and quality teams, aiming to improve data accuracy, quality scores, and appropriate reimbursement without adding clinician workload.
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