Alnu Health seeks full-stack AI engineer for clinical systems in NYC

Alnu Health's job posting signals a deliberate departure from the prevailing approach to healthcare AI. Rather than adopting the largest available language model and wrapping a chat interface around it, the company articulates a systems engineering philosophy centered on clinical reliability, patient safety, and clinician augmentation. The posting emphasizes continuous model evaluation and architectural flexibility—the ability to assess, adopt, or replace models and strategies as better options emerge—rather than building organizational lock-in around any single model, provider, or framework.

The technical requirements reflect this philosophy: the ideal candidate has not just deployed LLM APIs but has engineered production systems incorporating RAG (retrieval-augmented generation), embeddings, structured retrieval, tool orchestration, and evaluation frameworks for nondeterministic software. Equally important, the candidate must understand the distinction between semantic proximity in vector similarity and clinical relevance in patient context, and must be able to design feedback loops that turn clinical expert review into measurable system improvements. The emphasis on longitudinal patient memory, deterministic constraints, and observability suggests Alnu is solving problems of consistency and auditability that generic chat interfaces cannot address.