Data & AI Engineer II

Remote - US Full Time US$108K - US$135K Yearly Published on September 05, 2026 CareDx, Inc. caredx.com CareDx is a leading precision medicine diagnostics company advancing care in transplant, specialty oncology, and cell therapy. Through non-invasive longitudinal molecular biomarker testing, digital health, and patient support solutions, CareDx is dedicated to improving patient outcomes. For more information, please visit www.caredx.com. Our Mission: Create life-changing solutions that enable patients to thrive. Our Vision: A world where every patient receives the care they need to live longer, fuller lives. CareDx, Inc. is a leading precision medicine solutions company focused on the discovery, development, and commercialization of clinically differentiated, high-value healthcare solutions for transplant patients and caregivers. CareDx offers products, testing services, and digital healthcare solutions along the pre- and post-transplant patient journey, and is the leading provider of genomics-based information for transplant patients. The Data & AI Engineer II will develop analytical applications, data pipelines, and AI-powered capabilities that support clinical research, statistical analysis, and data-driven decision-making. This role helps transform research workflows, statistical analyses, and machine learning models into reliable, secure, and user-facing software. The engineer will collaborate with data scientists, statisticians, engineers, clinicians, and product stakeholders to productionize analytical workflows, translate R-based analyses into maintainable Python, and deliver applications for internal and external users. The engineer will also contribute to AI-powered features that analyze structured and unstructured data, extract information from documents, synthesize analytical results, and help users interpret scientific and clinical information. Success in this role requires strong software engineering fundamentals, curiosity, and the ability to independently deliver well-defined components and features with support on more complex technical decisions. Responsibilities: Develop and maintain analytical applications using tools and frameworks such as Python, Streamlit, Plotly, Dash, and Django. Own the implementation, testing, deployment, and maintenance of well-defined application features and data workflows. Productionize statistical models and machine learning workflows developed by data scientists and statisticians. Translate and refactor R-based research and analytical workflows into maintainable, tested Python code. Build and maintain data pipelines that support clinical data processing, analysis, visualization, and reporting. Develop interactive applications that enable data exploration, visualization, and decision support. Integrate applications with relational databases, APIs, analytical outputs, documents, and other structured and unstructured data sources. Contribute to AI-powered application features using techniques such as structured information extraction, retrieval-augmented generation, tool or function calling, and multi-step workflows. Implement validation, grounding, logging, traceability, and human-review mechanisms for AI-generated outputs. Collaborate with scientists, clinicians, product stakeholders, and senior engineers to translate requirements into practical technical solutions. Participate in technical design discussions and document implementation decisions, assumptions, and tradeoffs. Write reliable, readable, and testable code using established engineering patterns and team standards. Participate in code reviews and incorporate feedback to improve implementation quality and technical judgment. Monitor, debug, and improve application performance and reliability across data, model, AI, and application layers. Follow security, privacy, and compliance requirements for sensitive healthcare data, including HIPAA-aligned practices. Contribute to shared components, documentation, development too