Applied AI Engineer – Life Sciences, Healthcare

🕒 April 3

🏄 California, New York, +1 more states – Remote

🏄 California – Remote 🗽 New York – Remote 🤠 Texas – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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Vi

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

☁️ SaaS

Artificial Intelligence • Healthcare Insurance • SaaS

Vi is a company that leverages artificial intelligence to help health organizations improve member health outcomes and financial returns. The company provides an AI SaaS platform that offers solutions for efficient acquisition, personalized engagement, and predictive retention throughout the member lifecycle. Vi focuses on maximizing acquisition, enrollment, engagement, retention, upsells, and health outcomes with superior ROI. Their platform is designed to lower the cost per acquisition, enhance member engagement and retention, and transform operations with their generative AI technology. Vi works with leading global health enterprises to drive results at scale while ensuring privacy and data security standards are met.

📋 Description

• Build and deploy AI-powered voice and messaging agents for healthcare and life sciences clients, end-to-end. • Own client-facing technical relationships: translate business workflows into agent configurations, integration specs, and production systems. • Integrate with client data systems including CRMs, EHR/EMR platforms, specialty pharmacy systems, claims and Rx data feeds and build the ingestion pipelines to support them. • Write production backend services (TypeScript) and routing/ML logic (Python). • Design and maintain databases (relational and caching layers) that support both real-time agent operations and compliance audit trails.

🎯 Requirements

• 5+ years in a production engineering role shipping customer-facing software. • Fluency in TypeScript and Python. • Experience building and operating real-time systems: WebSockets, streaming media, event-driven architectures, or high-throughput API services. • Production integration work with CRM platforms (Salesforce, HubSpot, or similar), healthcare data systems (EHR/EMR, claims, pharmacy), or data warehouse/lake connectors (Snowflake, Databricks, S3). • Solid database fundamentals: relational schema design, query optimization, caching strategies. • Working knowledge of data engineering patterns: ETL/ELT pipelines, data quality checks, ingestion from heterogeneous sources. • Comfort with cloud infrastructure (AWS, GCP): containers, CI/CD, monitoring, and basic security practices. • Ability to work within HIPAA-regulated environments. • Strong client-facing communication.

🏖️ Benefits

• No explicit benefits listed