AI Principal Engineer - Clinical Data Analytics
About The Position
The AI Principal Engineer - Clinical Data Analytics is a leader responsible for building and scaling data engineering and AI capabilities across the Development organization. This incumbent acts as a strategic business partner across Data Science and Statistics (DSS) functions, integrating data across domains to generate actionable, outcome-driven insights and AI capabilities, including Generative and Agentic AI. Owns data architecture, governed data products, and cloud-native engineering patterns that enable analytics, machine learning, and Generative AI use cases in a regulated environment. Combines hands-on technical depth in data engineering and AI engineering with strong operational discipline across platform reliability, security, governance and lifecycle management. The role combines strategic vision, deep technical expertise, strong governance discipline and hands-on execution, enabling Exelixis to responsibly leverage data engineering, advanced analytics and AI in a highly regulated environment.
Requirements
- Bachelor's degree in Computer Sciences, Data in a related field (e.g., Information Services, Data Science) or equivalent and a minimum of eleven years of related experience; or, Master's degree in Computer Sciences, Data in a related field (e.g., Information Services, Data Science) or equivalent and a minimum of nine years of related experience; or, Equivalent combination of education and experience.
- Advanced experience with Databricks, Unity Catalog, Delta Lake and lakehouse governance.
- Advanced proficiency in Python and SQL; working knowledge of R if needed.
- Intermediate knowledge and enterprise experience leading data acquisition, analytics, and AI-based capabilities across multiple clinical domains.
- Intermediate knowledge of Delta Lake, Data Modeling Best Practices and Delta Lakehouse architecture.
- Intermediate knowledge of Metadata Management and Data Lineage Tracking in Unity Catalog.
- Intermediate knowledge of Enterprise Data Governance Methodologies and Data Cataloging Tools (e.g., Atlan, Colibra, Reltio).
- Advanced skills in developing and administering BI platforms, including Spotfire, Tableau, and Power BI.
- Advanced technical expertise in SaaS AWS Cloud Infrastructure, including SE, EC2, Lambda, Glue, Redshift.
- Intermediate skills with CI/CD Tooling and Version Control as part of Data Pipeline and Data Integration strategies.
- Intermediate abilities in Data Modeling and Warehouse Infrastructure Architecture.
- Advanced knowledge and abilities in Data Modeling, Data Integration Development, DevOps and Data Governance.
- Intermediate knowledge and skills in administering and developing with classified sensitive data and analytical products.
- Advanced knowledge and ability to provide data services and system ownership in a GxP-governed enterprise setting.
- Intermediate knowledge of Databricks maintenance and monitoring implementation strategies.
- Advanced knowledge of pharmaceutical and/or CRO industry practices with broad experience in one or more of the domains of Clinical Data Strategy and Insights.
- Advanced interpersonal, influencing, presentation, written and verbal communication skills.
- Advanced organizational and time management skills.
Responsibilities
- Develop production AI/ML and Generative AI solutions, including evaluation, deployment, monitoring and lifecycle management.
- Partner with business leaders to identify, scope, prioritize and deliver high-impact, outcome-driven analytics and AI use cases.
- Lead MLOps/LLMOps practices for model deployment, prompt/version management, monitoring and governance.
- Standardize reusable data models, semantic layers, and APIs for downstream analytics and AI applications.
- Serve as a trusted advisor to functional leaders, translating business questions into data and analytics solutions.
- Enable timely, data-driven decision-making through harmonized metrics, KPIs and insight frameworks.
- Effectively contributes highly developed analytical skills, conceptual thinking and integrative vision required to drive customer needs, business performance and risk management.
- Strong ability to explain technical concepts to non-technical members of the organization.
- Demonstrate strong understanding of AI/ML models, model performance, efficiency and algorithm explainability.
- Establish best practices for prompt engineering, AI usage training and model governance to ensure safe, effective adoption.
- Collaborate with Legal, Compliance and Security teams to ensure AI solutions meet regulatory and ethical standards.
- Design, implement and evolve modern data architectures, including data warehouses, data lakes and data pipelines.
- Ensure scalable, reliable and high-performance data platforms in collaboration with infrastructure and IT teams.
- Evaluate, select and optimize data management, analytics and AI technologies and tools.
- Performs other duties as assigned
- Complies with all policies and standards
Benefits
- 401k plan with generous company contributions
- group medical, dental and vision coverage
- life and disability insurance
- flexible spending accounts
- discretionary annual bonus program
- opportunity to purchase company stock
- long-term incentives
- 15 accrued vacation days in their first year
- 17 paid holidays including a company-wide winter shutdown in December
- up to 10 sick days throughout the calendar year
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What This Job Offers
Job Type
Full-time
Career Level
Principal
