Healthcare engagement platform for plans, providers, and health services
Carenet Health operates a healthcare engagement and care management platform serving 500+ health plans, providers, and health service organizations across the US and globally. The tech stack is enterprise-focused (Salesforce, Azure, AWS, Kubernetes, SQL Server) with a notably support-heavy hiring profile (22 support roles against 7 engineering) — reflecting a B2B services model centered on client success and operational delivery rather than rapid product iteration. Active projects span food-as-medicine programs, API library development, and proposal engine improvements, while pain points center on scaling enterprise sales, delivery predictability, and compliance automation (SOC 2, HIPAA, HITRUST).
Notable leadership hires: Technical Engagement Lead, Proposal Lead
Founded in 1988 and headquartered in San Antonio, Carenet Health is a privately held healthcare technology company with 1,001–5,000 employees. The company delivers patient engagement, care management, and telehealth solutions to health plans, providers, and health services organizations. According to the company, approximately one in three Americans have access to Carenet solutions through its relationships with 500+ client organizations. The platform addresses consumer healthcare engagement, gap closure in care delivery, and population health management across Medicare Advantage, Medicaid, and commercial health plans. Operations span the United States, Philippines, and Trinidad and Tobago.
Carenet uses Salesforce for CRM, Azure and AWS for cloud infrastructure, Kubernetes and Docker for containerization, GitHub Actions and Jenkins for CI/CD, Datadog and New Relic for monitoring, and SQL Server and MySQL for databases. Development languages include Python, C#, PHP, and PowerShell.
Key operational challenges include cost efficiency, delivery predictability, scaling enterprise sales, and compliance automation (SOC 2, HIPAA, HITRUST). Internally, teams face last-minute edits, data labeling for ML initiatives, and streamlining administrative workflows across complex, long-cycle B2B sales processes.
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