AI Agent Engineer - Patient Intake

Role Overview

We’re looking for an AI Agent Engineer to build intelligent systems that improve the patient-intake journey.

You will develop agents that help practices manage inquiries, collect information, verify requirements, coordinate follow-up, identify missing steps, and guide families through complex intake workflows. These agents must be useful, responsive, empathetic, and dependable while operating within clear privacy, safety, and escalation boundaries.

You will work across agent architecture, backend systems, integrations, evaluation, and product experience. The ideal candidate has built agents before and understands that a successful production agent requires much more than a strong prompt: it requires thoughtful tool design, workflow modeling, observability, evaluation, and ongoing iteration.

What You’ll Do

• Design and ship AI agents that support patient and caregiver intake workflows
• Build multi-step agents that collect information, answer questions, coordinate tasks, and move cases toward successful admission
• Integrate agents with scheduling systems, practice data, communication channels, APIs, and internal workflow tools
• Design conversational and non-conversational agent experiences that are clear, empathetic, and easy to use
• Develop tools, state models, and orchestration logic for long-running workflows that may span multiple interactions
• Establish escalation paths for clinical, operational, privacy, and safety-sensitive situations
• Build evaluations for accuracy, completion, tone, safety, user experience, and downstream operational outcomes
• Analyze agent traces and user behavior to identify failure patterns and improve performance
• Partner directly with intake coordinators, practice leaders, product managers, designers, and engineers
• Balance automation with human judgment by designing effective review and handoff experiences
• Implement monitoring and safeguards for production reliability
• Help establish reusable agent infrastructure and best practices across Hipp

What We’re Looking For

• Hands-on experience building AI agents, agentic products, or advanced LLM-powered applications
• Familiarity with common agent patterns, including tool use, routing, planning, retrieval, memory, structured outputs, and human escalation
• Strong software engineering skills and experience building production-quality systems
• Proficiency in Python, TypeScript, or a comparable programming language
• Experience integrating APIs, databases, messaging systems, or workflow services
• Experience designing, testing, and improving LLM behavior using systematic evaluations
• An understanding of common agent failure modes, including hallucination, tool misuse, context loss, looping, and brittle orchestration
• Strong product instincts and empathy for users navigating unfamiliar or stressful processes
• Ability to translate ambiguous real-world workflows into clear technical systems
• Strong written communication and collaborative problem-solving skills
• Comfort operating with autonomy and iterating quickly based on customer feedback

Additional information

There is no fixed years-of-experience requirement. We are looking for evidence that you have meaningfully built, tested, and improved agents-not simply experimented with model APIs.

Nice to Have

• Experience building conversational agents, customer-support automation, or communications workflows
• Experience with voice, SMS, email, or omnichannel agent systems
• Familiarity with healthcare intake, patient access, eligibility, referrals, or scheduling
• Knowledge of HIPAA, protected health information, consent, and data-minimization principles
• Experience building long-running or stateful agent workflows
• Familiarity with RAG, document extraction, knowledge systems, or identity resolution
• Experience building interfaces for human review, intervention, and escalation
• Early-stage startup experience