Senior AI Engineer

Most healthcare AI demos look incredible. In production, they hallucinate or get quietly ignored by the clinicians they were built for.

This role is about building the LLM systems that actually hold up inside clinical workflows.

You'll be joining the team building the operating system for value-based care — already used by leading primary care groups, ACOs, and health plans to act on real-time insights that improve outcomes and reduce costs across US healthcare.

You'll fine-tune and optimise LLMs for specific clinical use cases. You'll design RAG pipelines over real healthcare data, build knowledge graphs that integrate FHIR and HL7 standards, and evaluate model performance with the rigour HIPAA-bound environments demand.

You'll own the MLOps side too — production pipelines, monitoring, infrastructure for training and deployment. Not a research seat. A builder's seat.

Stack: Python, Huggingface, PyTorch, MLflow / Langfuse, AWS/GCP/Azure, Docker, Kubernetes. Plus deep work with FHIR, HL7, and HEDIS metrics.

You'll need proven LLM fine-tuning experience, hands-on RAG, sharp evaluation instincts (precision, recall, robustness), and real familiarity with healthcare regulatory ground — HIPAA at minimum, FHIR ideally.

Suitable for ex-ML founders, applied AI engineers tired of building consumer chatbots, or wildly ambitious continuous learners who want to ship into a regulated domain where the work actually matters.

Up to $180k. Hybrid, remote optional.

No CV required to start the chat. Message Kieran on LinkedIn to fast track.