Software Engineer II

Position Overview

We are looking for a Software Engineer, Revenue Cycle Management AI Automation & Platform to help build the next generation of Experity’s RCM technology.

In this role, you will design, develop, deploy, and operate production-grade software that supports critical healthcare revenue cycle workflows. You will work primarily across backend services, APIs, integrations, event-driven and long-running workflows, configurable business rules, and data, supporting areas such as charge entry, claims processing, claim submission, rejection and denial resolution, payments, and other parts of the revenue cycle.

You will work closely with Product Managers, RCM Operations, Software Engineers, Architects, Data teams, and QA to translate complex healthcare business workflows into scalable, maintainable software solutions.

This is a product engineering role where success means more than delivering features. You will help increase automation, reduce unnecessary manual work, improve claim outcomes, shorten processing time, and build an RCM platform that can continue to evolve.

You will be expected to understand the business workflow behind the software you build, identify opportunities for automation, and use deterministic software, configurable rules, data, and AI agent based on what is most appropriate for the problem.

What You’ll Do

· Design, develop, test, deploy, and operate scalable production software supporting Experity’s Revenue Cycle Management workflows.

· Build backend services and REST APIs using TypeScript, Node.js, and cloud-native technologies.

· Contribute to modern web applications when needed using technologies such as React, Next.js, and TypeScript.

· Design and implement event-driven, queue-based, and asynchronous workflows with explicit state management, retries, redrive, exception handling, idempotency, and auditability.

· Design long-running RCM workflows that support state transitions, human-in-the-loop processing, exception handling, replay/recovery, workflow versioning, and compensation or reversal when appropriate.

· Build integrations with Experity applications, healthcare clearinghouses, payer systems, and third-party RCM services.

· Design reliable interfaces for claims, payment, eligibility, rejection, denial, and other healthcare transaction workflows.

· Develop configurable business rules and workflow capabilities that replace logic currently distributed across application code, spreadsheets, and operational processes.

· Build rules and workflow capabilities that are configurable, versioned, explainable, auditable, and safe to change without introducing unnecessary application dependencies.

· Work with claims, financial, and operational data to improve automation, identify exceptions, and measure business outcomes.

· Integrate Generative AI, LLMs, agents, retrieval, and machine learning capabilities where they provide measurable value, while using deterministic software and business rules where those approaches are more appropriate.

· Build AI-enabled capabilities using clearly defined tools, APIs, contracts, permissions, validation, evaluation, observability, and fallback paths rather than treating LLMs as standalone solutions.

· Use modern AI-assisted software development practices for codebase exploration, development, testing, debugging, documentation, and engineering productivity while maintaining appropriate engineering review and quality standards.

· Build observability, automated testing, security, operational controls, and failure recovery into software from the beginning.

· Design systems with healthcare security, PHI protection, least-privilege access, auditability, and safe operational logging in mind.

· Contribute to architecture, technical design, engineering standards, and platform evolution.

· Collaborate with Product, RCM Operations, Architecture, Data, QA, and other engineering teams to understand real-world workflows and translate them into reliable software.

· Investigate production issues using application behavior, logs, metrics, data, and user workflows.

· Own software through production and continuously improve it based on system behavior, operational feedback, and business results.

· Measure the impact of engineering improvements through outcomes such as automation rate, exception rate, manual touches, processing time, rejection/denial resolution time, successful resubmission, payment outcomes, and system reliability.

Qualifications

Required

· 3+ years of professional software engineering experience building and supporting production applications.

· Strong software engineering fundamentals, including application design, testing, debugging, code review, and maintainability.

· Experience building backend services, REST APIs, and distributed applications.

· Proficiency with TypeScript, Node.js, or comparable modern backend technologies.

· Experience with modern web development technologies such as React, Next.js, or similar frameworks.

· Experience with relational databases, SQL, data modeling, and transactional systems.

· Experience developing and operating cloud-hosted applications, preferably on AWS.

· Understanding of asynchronous processing, queues, events, retries, idempotency, and distributed-system failure modes.

· Experience with automated testing, CI/CD pipelines, observability, and secure software development practices.

· Ability to break complex business workflows into well-defined software components, services, and contracts.

· Ability to investigate ambiguous problems and develop solutions using production behavior, data, logs, and user workflows rather than relying only on predefined requirements.

· Strong collaboration and communication skills with the ability to work across engineering, product, operations, architecture, and data teams.

Preferred

Experience in one or more of the following areas is valuable but not required:

· Healthcare Revenue Cycle Management, medical billing, claims, rejections, denials, eligibility, or payment processing.

· Healthcare, HealthTech, or SaaS environments.

· Waystar or other healthcare clearinghouse integrations.

· High-volume transaction or workflow-processing systems.

· Event-driven architectures and distributed systems.

· Modernizing legacy systems incrementally while maintaining production continuity.

· Configurable rules engines, workflow orchestration systems, or exception-management platforms.

· Production use of Generative AI, LLMs, AI agents, retrieval-augmented generation, or machine learning.

· AI orchestration frameworks, structured tool use, MCP or similar tool protocols, and agentic workflows.

· Build human-in-the-loop automation where AI or software recommendations require review, approval, correction, or escalation.

· Snowflake or other cloud-native data platforms.

· Docker, Kubernetes, and containerized application deployment.

· Data-intensive application development and distributed data processing.

Technology Environment

Our RCM engineering environment includes:

· Backend: TypeScript, Node.js, Python

· Frontend: React, Next.js, TypeScript, Tailwind CSS

· Cloud & Platform: AWS, Docker, Kubernetes, CI/CD

· Architecture: REST APIs, queues, events, asynchronous workflows, distributed services

· Data: SQL, Snowflake, Tableau

· AI: AWS Bedrock, LLM APIs, retrieval, structured tool use, Generative AI, and agentic workflows

· Integrations: Waystar, Experity EMR and Practice Management, payer systems, and third-party RCM services

Candidates are not expected to have experience with every technology listed above. Strong engineering fundamentals, relevant production experience, and the ability to learn new technologies and domains are more important than matching every item in the stack.

How We Work

We want engineers who understand the problem they are solving, not just the ticket they are implementing.

You should be comfortable learning a complex healthcare domain, questioning existing processes, working through ambiguity, making practical technical tradeoffs, and taking ownership of the software you build.

Our engineers collaborate closely with business and operational teams because understanding the real workflow is essential to building the right solution. We value pragmatic engineering, measurable outcomes, incremental modernization, and choosing the right technology for the problem rather than applying technology for its own sake.

We expect engineers to think beyond individual features: understand the end-to-end RCM workflow, identify where AI and automation can eliminate unnecessary work, design for exceptions and failure from the beginning, and measure whether the software actually improves operational and financial outcomes.

We are also building an AI-native engineering culture. Engineers are expected to use modern AI development tools thoughtfully to accelerate delivery and improve quality while retaining ownership of architecture, code quality, testing, security, and production outcomes.

Equal Opportunity Employer

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