Agent Engineer

About Hipp

Hipp is an AI-native healthcare platform built to modernize operations for non-hospital healthcare providers. We partner closely with ambulatory healthcare organizations to streamline clinical workflows, billing, revenue cycle operations, scheduling, and patient engagement—so providers can spend less time managing administrative work and more time delivering care.

Our platform combines EMR capabilities, billing infrastructure, operational workflows, and AI agents in one intelligent system. We are building the next generation of healthcare infrastructure and are looking for thoughtful, product-minded engineers who want to solve complex problems, ship quickly, and take meaningful ownership.

Role Overview

We’re looking for an Agent Engineer to build intelligent agents that help healthcare practices manage billing, compliance, and day-to-day operations.

You will develop production agents that can understand complex compliance and practice-management workflows, retrieve and reason over operational data, use tools safely, and take reliable action. These systems will support workflows such as patient intake, payor compliance, claim preparation, billing follow-up, payment reconciliation, task prioritization, exception handling, and operational reporting.

This is not a research-only or prompt-writing role. You will own agentic systems end to end—from workflow discovery and architecture through tool integration, evaluation, deployment, monitoring, and continuous improvement.

What You’ll Do

• Design and ship production AI agents for billing, compliance, and practice-management workflows

• Translate complex, multi-step operational processes into reliable agent workflows

• Build tools and integrations that allow agents to interact safely with billing systems, practice data, APIs, queues, and internal services

• Develop orchestration patterns for planning, routing, tool selection, retries, escalation, and human review

• Build evaluation suites that measure task completion, accuracy, reliability, latency, cost, and operational impact

• Create guardrails and approval mechanisms for actions involving claims, payments, patient information, or sensitive practice data

• Investigate production failures using traces, logs, conversation histories, and tool-call data

• Partner closely with billing experts, customers, product managers, and engineers to understand real workflows and identify opportunities for automation

• Design systems that know when to act autonomously, when to ask for clarification, and when to escalate to a human

• Improve agent performance through prompt iteration, tool design, context engineering, retrieval, model selection, and workflow redesign

• Own features from initial discovery through launch, monitoring, and iteration

What We’re Looking For

• Demonstrated experience building AI agents, agentic applications, or sophisticated LLM-powered workflows

• Experience building systems that use tools, APIs, structured outputs, retrieval, memory, or multi-step reasoning

• Strong software engineering fundamentals and the ability to ship maintainable production code

• Proficiency in Python, TypeScript, or another language used to build production backend systems

• Experience designing and integrating APIs, databases, asynchronous jobs, and external services

• A strong understanding of where LLMs are effective—and where deterministic logic, validation, or human review is necessary

• Experience evaluating agent behavior beyond anecdotal testing

• Comfort debugging nondeterministic systems and turning failure patterns into measurable improvements

• Strong product judgment and an interest in understanding how users actually perform their work

• Clear communication and the ability to collaborate with both technical and operational stakeholders

• A high degree of ownership, curiosity, and comfort working in an evolving startup environment

We care more about what you have built and how you think than a specific number of years in the industry. Professional work, open-source contributions, substantial independent projects, and research translated into working systems are all relevant.

Nice to Have

• Experience with healthcare billing, revenue cycle management, claims, remittance, eligibility, or practice-management systems

• Familiarity with healthcare data, HIPAA requirements, or regulated workflows

• Experience with agent frameworks, model APIs, tracing platforms, or evaluation tooling

• Experience implementing human-in-the-loop workflows and approval systems

• Familiarity with RAG, structured extraction, document processing, and long-running agent workflows

• Experience operating AI systems with real users and meaningful reliability requirements

• Startup experience or experience working on a small, high-ownership engineering team

Why Join Hipp

• Build AI agents that perform real work for healthcare providers

• Solve complex operational problems with measurable customer and business impact

• Join an early engineering team and help define Hipp’s agent architecture and engineering practices

• Work directly with product leaders, domain experts, founders, and customers

• Build at the intersection of AI, healthcare infrastructure, billing, and workflow automation

• Own important systems from concept through production