Data & AI Engineer II

CareDx, Inc. develops precision medicine solutions for transplant patients. The Data & AI Engineer II builds and maintains analytical applications, data pipelines, and AI-powered features, productionizing research workflows and models for clinical research and data-driven decision-making.

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 tools, and engineering process improvements
• Communicate progress, risks, dependencies, and technical challenges clearly and proactively

Requirements:

• Bachelor's or master's degree in Computer Science, Data Science, Engineering, Biostatistics, or a related quantitative field, or equivalent practical experience
• 2+ years of experience in data engineering, backend engineering, full-stack development, analytics engineering, or a related role
• Strong proficiency in Python for data analysis and software development
• Experience working with statistical analysis, data science, or machine learning workflows
• Experience transforming prototype, research, or analytical code into maintainable software
• Experience building analytical applications using Streamlit, Plotly, Dash, or similar technologies
• Experience developing backend services or web applications using Django, FastAPI, Flask, or a similar framework
• Experience building and maintaining data pipelines that integrate multiple data sources
• Familiarity with relational databases, SQL, APIs, and common data formats
• Experience or demonstrated applied knowledge in at least one modern LLM capability, such as retrieval-augmented generation, structured extraction, tool calling, or agentic workflows
• Understanding of core production considerations for AI systems, including grounding, hallucination mitigation, output validation, security, latency, cost, and human oversight
• Experience with version control and collaborative development practices, including Git, branching, pull requests, and code reviews
• Experience writing automated tests and debugging applications across multiple technical layers
• Ability to independently deliver well-defined features while seeking guidance when requirements or technical risks are unclear
• Strong written and verbal communication skills
• Honest and transparent approach to feedback, collaboration, and accountability
• Experience in healthcare, biotechnology, clinical research, or another regulated environment
• Experience working with sensitive or protected healthcare data
• Familiarity with HIPAA-aligned application and data-handling practices
• Experience with Azure, Databricks, or comparable cloud and data platforms
• Familiarity with CI/CD practices and automated testing tools such as pytest
• Experience with pandas, NumPy, scikit-learn, statsmodels, or similar data science libraries
• Experience deploying or supporting production web applications
• Experience using modern AI-assisted software development tools, such as Codex or similar coding agents, for development, testing, debugging, and documentation
• Domain knowledge in biological medicine, healthcare, or clinical data
• Experience communicating technical work to scientific or clinical audiences