AI Agent Engineer for Healthcare Compliance & Automation

OpenKrill; United States; Remote; USD 140.000 - 175.000; Vollzeit

Zusammenfassung

Hipp is seeking an AI Agent Engineer to build systems that help healthcare practices operate accurately and in compliance with payer requirements. You will develop agents that review documentation, identify gaps, apply policies, explain findings, and guide users toward resolution.

You will also build evaluation, audit, and human-review infrastructure for high-stakes environments, with emphasis on reliability, explainability, and auditable decision trails.

Qualifikationen

• Demonstrated experience building AI agents, agentic systems, or substantial LLM-powered products.
• Strong software engineering skills and the ability to build secure, maintainable production systems.
• Experience grounding AI systems in authoritative source material.

Aufgaben

• Design and ship AI agents for documentation review, workflow compliance, policy checks, and operational quality assurance.
• Convert complex requirements into testable agent workflows, tools, policies, and decision boundaries.
• Build retrieval systems that ground agent behavior in approved policies, contracts, payer rules, and internal guidance.
• Develop structured review workflows that surface missing information, inconsistencies, exceptions, and recommended next actions.
• Create clear citations, evidence trails, and audit logs for agent outputs and actions.
• Design human-review and approval mechanisms for high‑risk or ambiguous decisions.
• Build rigorous evaluations for factual grounding, policy adherence, consistency, recall, precision, and safe escalation.

Kenntnisse

AI agents

Python

TypeScript

Observability

Jobbeschreibung

Hipp is seeking an AI Agent Engineer to build systems that help healthcare practices operate accurately and in compliance with payer requirements. You will develop agents that review documentation, identify gaps, apply policies, explain findings, and guide users toward resolution.

You will also build evaluation, audit, and human-review infrastructure for high-stakes environments, with emphasis on reliability, explainability, and auditable decision trails.