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Vi is hiring a Senior Applied AI Engineer to build and deploy production AI agents for healthcare and life sciences clients. You'll own the full stack: from understanding client workflows and translating them into agent designs, to building real-time voice and messaging systems, integrating with healthcare data systems (EHR/EMR, CRMs, pharmacy platforms), and ensuring HIPAA compliance.
Key responsibilities include designing and deploying AI-powered agents end-to-end; running technical sessions with enterprise customers to convert clinical and operational workflows into agent configurations; building data ingestion pipelines from diverse healthcare sources; writing production infrastructure in TypeScript (agent runtime, routing, orchestration) and Python (training, embeddings); implementing guardrails and compliance controls; designing databases supporting real-time operations and audit trails; and codifying client patterns into reusable platform components.
You'll work closely with product, account management, and platform engineering to translate field learnings into platform improvements. This is a client-facing role requiring strong technical communication and the ability to translate customer needs into engineering decisions.
Required: 5+ years shipping production customer-facing software (solutions engineering or consulting backgrounds acceptable if you wrote and deployed code); fluency in JavaScript/TypeScript/Python; experience building real-time systems (WebSockets, streaming, event-driven architectures); production integration work with CRM platforms (Salesforce, HubSpot) or healthcare data systems; experience building retrieval and ingestion pipelines with proper guardrails and caching; data engineering patterns (ETL/ELT, data quality, heterogeneous source ingestion); cloud infrastructure comfort (AWS/GCP, containers, CI/CD, security); ability to work within HIPAA constraints; strong client-facing communication skills; startup disposition with low ego and high agency.
Nice-to-have: voice/telephony infrastructure experience; LLM orchestration and agentic system design; healthcare/life sciences domain knowledge; workflow or rules engine experience; product sensibility; prior healthcare tech or AI-native startup experience.
