Arcadia Staff Applied AI Engineer at Arcadia responsible for owning product-layer decisions shaping agent behavior in healthcare AI workflows. This role focuses on improving reliability, calibration, and cost of agentic capabilities at scale.
Responsibilities
You have established a production-grounded baseline for priority agentic workflows, with documented failure modes, severity-weighted evaluation rubrics, and a clear measurement plan
You have mapped the current retrieval, context, memory, and escalation patterns and identified the highest-value opportunities to improve reliability, calibration, and cost
You have earned trust across Product and Engineering by turning production evidence into clear, actionable recommendations
Production-representative evaluation suites and regression checks inform model-change decisions for priority agentic workflows
Qualification
Model cards
Required
You have delivered measurable improvements in accuracy, reliability, steerability, latency, or cost for one or more priority workflows
Human-review and escalation behavior has been validated under adversarial and edge-case conditions, with decision criteria and ownership boundaries clearly documented
Arcadia has a repeatable product-layer AI performance practice that moves from production failure to diagnosis, experiment, evaluation, and release decision
High-severity regressions are caught earlier, and agent behavior is more transparent, calibrated, and trustworthy at scale
Model cards, intended-use guidance, limitations, and performance documentation are current and useful to product and customer-facing teams
