Staff Software Engineer, AI Engineering

Tebra only initiates contact with candidates via email from an official Tebra email address (@tebra.com, @patientpop.com, or @kareo.com) or through our applicant tracking system, Greenhouse. We will only ask you to provide sensitive personal information through our official application portal — not via social media or text message. We do not conduct interviews via instant messaging.About the Role The Revenue Cycle Management (RCM) team is seeking a Staff Software Engineer to lead the design, development, and adoption of AI-native capabilities across our billing and revenue cycle platform. This role combines deep software engineering expertise with hands-on experience building production AI systems. You will help transform how healthcare organizations manage billing, payments, claims, and operational workflows by applying Large Language Models (LLMs), intelligent automation, retrieval systems, and agentic AI architectures to solve real-world business problems. As a senior individual contributor, you will operate at the intersection of platform architecture, AI systems engineering, and business transformation. You will influence technical strategy across teams, design reusable AI capabilities, and establish engineering standards for building reliable, secure, and scalable AI-powered systems. Your impact will come through technical leadership, architectural ownership, hands-on implementation, and your ability to translate complex business challenges into intelligent software solutions that deliver measurable outcomes. Your Area of Focus Identify and implement practical opportunities to embed AI into backend services and business workflows where it can improve efficiency, accuracy, or decision support. Design and build production-ready AI-enabled services that combine application logic, APIs, and AI models to support real customer and operational use cases. Integrate LLMs, ML models, and external AI services into existing systems using strong engineering patterns for reliability, observability, and maintainability. Build workflows that use AI in a bounded, auditable way, with clear fallback behavior, evaluation, and human review where appropriate. Partner with product, design, data, and operational teams to turn workflow pain points into scalable software solutions with measurable impact. Lead Software Development: Design, develop, test, and deploy scalable and maintainable software applications using Spring Boot, Java, React, and cloud technologies. Architect and Design: Collaborate with product managers, designers, and cross-functional teams to architect robust and scalable solutions that meet business requirements. Provide input into the technical direction of the team and product. Cloud Technology Expertise: Leverage experience with cloud platforms (AWS, Azure, Google Cloud, etc.) to design cloud-native applications. Ensure that applications are optimized for scalability, reliability, and cost-efficiency in a cloud environment. Code Revie...