AI Agent Developer
HonorHealth
- Location
- Hybrid (Virtual - Arizona, Arizona)
- Employment
- Full-time
- Level
- Mid Level
About the Role
HonorHealth, a leading nonprofit healthcare system in Arizona, seeks an AI Agent Developer to design and build secure, governed AI agents and workflows. This role focuses on integrating agents with enterprise systems to enhance productivity and decision-making within regulated healthcare environments.
Skills
Full job details
Primary City/State:
Virtual ArizonaCategory:
Data IntelligenceShift:
DayDepartment:
Augmented Intelligence

Hours: Monday-Friday Days
Location: Remote -- Must be located in Arizona -- Occasional on site as needed.

Great care starts with great people. (Like you.)
At HonorHealth, you’ll find something special. From humble beginnings in 1927 to one of Arizona’s largest nonprofit healthcare systems, our culture is built on warmth and neighborly kindness. Behind every smile is a highly skilled professional with deep expertise and an unwavering dedication to what matters most — caring for the health and well-being of people and communities across the greater Phoenix area.
Responsibilities:

- Agent Design and Development: Design and build AI agents and agent-enabled workflows using approved enterprise platforms, APIs, orchestration tools, and large language model capabilities. Translate business requirements into agent logic, task definitions, prompt structures, decision paths, and interaction patterns. Develop agent behaviors for multi-step reasoning, content retrieval, workflow support, and task execution within approved boundaries. Configure agent inputs, outputs, memory patterns, permissions, and interaction rules based on intended use.
- Tool, Data, and System Integration: Connect agents to approved enterprise tools, systems, APIs, knowledge bases, workflow platforms, and data sources. Build and maintain integrations that enable secure and reliable information retrieval or task support. Collaborate with technical teams to ensure connectivity, authentication, data flow, and architecture alignment support intended agent behavior. Help define reusable patterns for agent integration across multiple use cases.
- Testing, Evaluation, and Reliability: Develop and execute test plans for AI agent behavior, edge cases, workflow reliability, and failure recovery. Monitor agent outputs, tool calls, workflow consistency, and production behavior to identify issues, drift, or reliability concerns. Debug agent failures, integration errors, prompt breakdowns, or logic conflicts and implement corrective improvements. Support controlled rollout and stabilization of new agent capabilities.
- Governance, Security, and Guardrails: Ensure agent configurations operate within approved governance, access, privacy, and security boundaries. Implement controls that support safe use, role-based access, escalation limits, and transparent handling of sensitive information. Partner with governance, privacy, compliance, or security stakeholders when agent workflows intersect with regulated or high-risk use cases. Document intended scope, limitations, approved sources, and operational guardrails for deployed agents.
- Documentation and Technical Standards: Create and maintain technical documentation for agent architecture, integration design, configuration logic, deployment steps, and change history. Support coding standards, reproducibility, maintainability, and reusable design patterns across agent implementations. Contribute to technical best practices for AI-enabled workflow development and lifecycle support.
- Cross-Functional Collaboration and Improvement: Partner with AI Trainers, software engineers, analysts, product/initiative leads, and subject matter experts to improve deployed agent performance and utility. Translate feedback from users and stakeholders into technical enhancements, configuration changes, or architecture improvements. Support ongoing maturation of enterprise AI-agent capabilities through disciplined iteration and lessons learned.
- Performs other duties as assigned
- Bachelors in Computer Science or 4 years equivalent experience, Software Engineering, Information Systems, Data Engineering, or related field Required
- Masters in Computer Science, Artificial Intelligence, Data Science, or related field Preferred
- 2 years, Experience with APIs, application integration, cloud-based platforms, or workflow orchestration Required
- 3 years, Software engineering, systems integration, workflow automation, AI application development, or related experience Required
- , Experience with LLM-enabled applications, prompt design, retrieval patterns, agent frameworks, or tool-calling architectures Preferred
- , Experience in healthcare, HR, or other regulated enterprise environments Preferred
- , Experience with Microsoft Copilot Studio and/or Google Cloud Platform (GCP) AI tools Preferred
- Relevant cloud, AI platform, or software engineering certifications Preferred
We're all in for your career.