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The RCM Client Success Manager is responsible for managing client relationships post-onboarding, ensuring client satisfaction in clinical, administrative, and billing workflows while identifying growth opportunities within revenue cycle management.

Own Prompt's API and EHR integration roadmap, manage interoperability with major EHRs and Kno2, lead Patient Portal development, guide DevOps priorities, ensure CEHRT/CMS/HIPAA compliance, and coordinate cross-functional product, engineering, sales, and partner initiatives.

Provide executive assistant support to the CS VP and operational support to the Customer Success team, managing onboarding projects, CRM and data transfer tasks, tracking KPIs, documenting processes, using Asana and Excel, and coordinating cross-functional activities to improve onboarding and client operations.

The Associate Client Success Manager will build client relationships, ensure product usage, provide support, and contribute to onboarding and training for rehab therapy teams.

The Accounts Receivable Specialist manages billing and collections for medical services, ensuring compliance and prompt payment from insurance and patients, while resolving claim issues.

The Senior Data Engineer will design and develop data systems and pipelines, perform analyses, and collaborate with stakeholders to improve decision-making in healthcare.

The Senior Full Stack Software Engineer will oversee technical development in a B2B SaaS healthcare environment, mentor junior engineers, and lead product features.

The Payment Posting and AR Specialist will post and reconcile insurance and patient payments, resolve errors, and manage Accounts Receivable tasks while maintaining accurate ledgers.

Identify and engage rehab therapy prospects via cold calling, email, and social media; schedule and deliver tailored product demos; build relationships with healthcare professionals; collaborate with sales, marketing, and product teams; attend industry events; evangelize EMR software and qualify leads to drive revenue growth.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.