L3 Senior Software Engineer, RPA

Scan.com•Atlanta, GA

18h•$200,000 - $255,000•Remote

About The Position

We’re Scan.com, the digital health scale-up making diagnostics accessible, fast, and transparent. Our technology speeds up diagnoses for timely treatments, improving healthcare outcomes for hundreds of patients each day. We're doing diagnostics differently, with solutions tailored to both patients and providers, all backed by our technology and world-class customer operations team. Our B2C marketplace simplifies booking a scan, making it as straightforward for patients as booking a hotel. Our B2B platforms provide live scheduling at the point of care and harness AI to ease workflows for physicians, attorneys, and providers. We’re looking for a Senior RPA Integration Engineer at an exciting time – we’ve successfully launched multiple platforms and products, raised over $100m in VC funding, reached profitability, and have a growth trajectory of over 100% YoY. Reporting to Humale, our Chief Product & Technology Officer, you’ll sit at the intersection of engineering and operations, building the automation layer that connects hundreds of imaging center scheduling systems to Scan.com’s internal platform. Your primary focus will be designing and deploying RPA solutions that extract appointment availability and scheduling data from the imaging center RIS (Radiology Information Systems) and accurately input that data into our product. This is a high-impact, high-autonomy role that directly drives operational efficiency and patient throughput across our national network. As a scaleup business, you can expect your role to develop over time. Here are some of the types of things you could be getting involved in:

Requirements

Production experience with RPA platforms such as UiPath, Automation Anywhere, or Power Automate, specifically building bots that interact with web-based and thick-client applications. Bonus if you’ve worked in Citrix or remote desktop environments
Proficiency in Python for scripting, data transformation, and extending RPA workflows beyond what native rolling supports.
An API-first mindset paired with RPA pragmatism: you default to HL7, FHIR, or direct API integration where available, but know when and how to fall back to UI automation
Hands-on familiarity with navigating healthcare RIS/PACS platforms, with an understanding of how appointment scheduling data is structured and surfaced across different vendor UIs
Strong skills in screen-scraping and data extraction from unstructured or inconsistent user interfaces, including building resilient selectors that survive vendor UI updates
A track record of designing robust error handling and exception management systems, including retry logic, alerting, and structured escalation workflows rather than bots that silently fail
Experience building data validation and reconciliation processes that confirm accuracy across systems
Strong documentation habits and a mindset oriented toward building for handoff, understanding that your work today creates the foundation for agentic AI automation
A testing mindset applied to automation: you write tests for your bots, and validate outputs systematically, and don't consider a workflow dont until failure modes are covered
Experience managing bot portfolios across dozens or hundreds of target systems, thinking in templatized architectures rather than one-off builds
Comfort navigating stakeholder relationships to secure system access and technical cooperation from external partners

Responsibilities

Design, build, and maintain RPA bots that extract appointment time data from imaging center RIS platforms and trigger downstream patient scheduling workflows
Navigate a diverse landscape of RIS systems, building resilient screen-scraping and data extraction logic that handles UI inconsistencies across vendors
Develop robust error handling and exception management architecture, including structured exception queues, retry logic, alerting, and human-in-the-loop escalation workflows
Build data validation and reconciliation layers that verify the accuracy of data transferred between systems, preventing downstream issues like appointment mismatches and scheduling errors
Partner with operations, engineering, and imaging center partners to secure system access, credentials, and the technical information needed to build effective integrations
Document all workflows, decision logic, edge cases, and process maps with the explicit goal of creating the foundation for future agentic AI automation