Applied AI Engineer

About this role

Re‑architecting U.S. healthcare demands speed, precision, and an obsession with details. Cadence is building a remote care delivery system that keeps older people healthy, out of the hospital, and at home. By pairing each patient with a dedicated clinical team that reviews their health every day, versus every few months, we catch issues early and intervene before they escalate. The result: measurably better outcomes for patients and less administrative burden for clinicians.


Today, Cadence supports tens of thousands of active patients nationwide. Our AI‑powered system and scalable clinical model enable proactive, population‑level care. We’re among the fastest‑growing companies in healthtech, and we’re just getting started.


We're looking for an Applied AI Engineer to design and ship production agents that synthesize real-time clinical data, surface proactive care recommendations, and take action on behalf of clinicians. You will take agent architectures from prototype to production in a domain where reliability directly affects patient outcomes.


You'll own the full lifecycle of AI-powered clinical workflows: retrieval, reasoning, tool use, evaluation, and safety guardrails. If you've built agentic systems at scale and want your work to matter beyond engagement metrics, we’d love to speak with you.


WHAT YOU’LL DO:

• Design, build, and deploy clinical AI agents that reason over patient context, invoke tools, and generate care recommendations.
• Own reliability, observability, and cost efficiency of LLM-powered workflows at scale.
• Build and optimize RAG pipelines over clinical knowledge bases, treatment protocols, and real-time patient data.
• Develop evaluation frameworks: offline benchmarks, safety tests, regression suites, and LLM-as-judge pipelines wired into CI/CD.
• Design multi-step agent orchestration: planning, memory, tool use, error recovery, and human-in-the-loop escalation paths.
• Collaborate with clinical, product, and engin...