Agent Engineer

Role overview Build production AI agents that help healthcare practices handle billing, compliance, and daily operations. You’ll own systems from workflow discovery and architecture through integrations, evaluation, deployment, and ongoing improvement, ensuring agents can use operational data and tools safely and reliably.

Responsibilities - Turn complex operational processes into dependable, multi-step agent workflows. - Build integrations with billing systems, practice data, APIs, queues, and internal services. - Design orchestration for planning, tool selection, retries, escalation, and human review. - Create evaluations that measure task success, accuracy, reliability, latency, cost, and operational impact. - Add safeguards and approval steps for sensitive actions involving claims, payments, or patient information. - Investigate production issues using traces, logs, conversation histories, and tool-call data; refine agents through testing and iteration.

Requirements - Demonstrated experience building AI agents or LLM-powered systems that do useful work. - Ability to design reliable software systems, integrations, and workflows from ambiguous operational needs. - Sound judgment about when an agent should act, request clarification, or hand work to a person. - Comfort assessing quality and reliability through evaluations and production observations. - Strong collaboration skills and willingness to take ownership in an evolving environment.

Nice to have - Experience with healthcare billing, claims, eligibility, remittance, or practice-management systems. - Familiarity with healthcare data, privacy requirements, or regulated workflows. - Experience with agent frameworks, model APIs, tracing, evaluation tools, or human approval flows. - Knowledge of retrieval-augmented generation, document processing, structured extraction, or long-running agents.