Data & AI Engineer II

CareDx, Inc. • Brisbane, CA

1d • $108,000 - $166,000 • Remote

About The Position

CareDx, Inc. is a precision medicine solutions company focused on clinically differentiated healthcare solutions for transplant patients and caregivers. The Data & AI Engineer II develops analytical applications, data pipelines, and AI-powered capabilities supporting clinical research, statistical analysis, and data-driven decisions. The role turns research workflows, statistical analyses, and machine learning models into reliable, secure, user-facing software, working with data scientists, statisticians, engineers, clinicians, and product stakeholders. It includes translating R-based analyses into maintainable Python, productionizing analytical workflows, and delivering applications for internal and external users. The engineer also contributes AI features for analyzing structured and unstructured data, extracting information from documents, synthesizing analytical results, and helping users interpret scientific and clinical information. The role calls for strong software engineering fundamentals, curiosity, and the ability to independently deliver defined components and features, with support on more complex technical decisions.

Requirements

• Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, Biostatistics, or a related quantitative field, or equivalent practical experience.
• At least 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 with statistical analysis, data science, or machine learning workflows.
• Experience transforming prototype, research, or analytical code into maintainable software.
• Experience building analytical applications with Streamlit, Plotly, Dash, or similar technologies.
• Experience developing backend services or web applications with Django, FastAPI, Flask, or a similar framework.
• Experience building and maintaining data pipelines integrating 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 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 defined features and seek guidance when requirements or technical risks are unclear.
• Strong written and verbal communication skills.
• Honest and transparent approach to feedback, collaboration, and accountability.

Nice To Haves

• 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.

Responsibilities

• Develop and maintain analytical applications using Python, Streamlit, Plotly, Dash, Django, and similar tools.
• Own implementation, testing, deployment, and maintenance of 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 pipelines supporting clinical data processing, analysis, visualization, and reporting.
• Develop interactive applications for data exploration, visualization, and decision support.
• Integrate applications with relational databases, APIs, analytical outputs, documents, and other structured and unstructured data sources.
• Contribute AI-powered features using 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, 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.

Benefits

• Competitive base salary and incentive compensation.
• Health and welfare benefits, including a gym reimbursement program.
• 401(k) savings plan match.
• Employee Stock Purchase Plan.
• Pre-tax commuter benefits.
• Up to 30 days of paid leave annually under the Living Donor Employee Recovery Policy for a full-time employee donating an organ or bone marrow.
• The role may be eligible for additional discretionary bonuses or incentives and restricted stock units.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level