Note: The job is a remote job and is open to candidates in USA. UCSF Health is seeking a Principal Research Software Engineer to serve as the primary technical expert supporting a nationally recognized health policy research program. The role involves designing and developing research software systems, leading AI strategy, and ensuring the usability and compliance of data platforms across various research collaborations.
Responsibilities
- Design, develop, test, debug, document, and maintain research software systems, data architectures, metadata management capabilities, and analytical infrastructure that enable researchers to discover, understand, integrate, access, and analyze complex datasets efficiently, reproducibly, securely, and at scale
- Modernize legacy systems and automate operational and research workflows to improve reliability, security, and efficiency across the program’s technology ecosystem
- Serve as the primary technical expert for major public, administrative, clinical, policy, and observational datasets used by the research program, developing deep expertise in their structure, provenance, strengths, limitations, and appropriate analytical applications
- Establish technical standards, architecture principles, engineering practices, code review and quality oversight processes, and governance approaches, adopted across the program and its collaborating institutions, that ensure the reliability, maintainability, reproducibility, and long-term sustainability of research technology assets
- Holds overall responsibility for the quality of the program’s software and data systems and their integration with institutional and external systems
- Evaluate, prototype, and responsibly deploy emerging artificial intelligence technologies that enhance research productivity, scientific discovery, data exploration, and analytical workflows, including both locally hosted open-weight models and externally hosted commercial models, within environments containing sensitive or regulated data
- This work has little or no precedent and requires formulating governance strategies and policies for the responsible use of AI with regulated health data, with significant influence on organizational policy and program development
- Develop AI-enabled tools and workflows supporting activities such as dataset exploration, variable discovery, cohort identification, literature synthesis, research workflow automation, natural language interaction with structured data, and research knowledge management
- Assess emerging AI, computational, and data technologies and identify opportunities where they can responsibly improve research quality, efficiency, reproducibility, and scientific impact
- Design and establish reusable technical capabilities that can support multiple research projects, datasets, investigators, and collaborating institutions
- Develop and maintain, in partnership with the Principal Investigator and research leadership, a multi-year technology roadmap that aligns software, data, AI, and computational investments with evolving scientific priorities
- Evaluate emerging opportunities, prioritize and direct technical investments, and formulate research technology strategy, administering the policies, processes, and resources of the program’s technology portfolio, to maximize scientific impact and long-term organizational capabilities
- Partner closely with investigators, research staff, and external collaborators to understand scientific objectives, provide guidance on the effective use of software, data, AI, and emerging technologies, and translate research needs into scalable technical capabilities
- Provide technical leadership for grant proposals, publications, presentations, collaborative research initiatives, and infrastructure planning efforts, helping identify and pursue funding opportunities that expand the program’s technical, computational, data, and AI capabilities through technical proposal development and research infrastructure design
- Provide technical leadership and consultation on software architecture, data systems, artificial intelligence, and emerging computational methods
- Direct and review the technical work of research staff, analysts, and other technical contributors within the program and across collaborating institutions; mentor technical staff and trainees; and promote software engineering best practices across collaborative projects
- Develop reusable software, data tools, standards, documentation, training materials, and educational resources, and contribute to shared research infrastructure, open-source initiatives, and open-science efforts that advance research collaboration and scientific impact, extending the program’s impact beyond the University to the broader research community
- Promote the responsible adoption of artificial intelligence, data, and computational methods through consultation, demonstrations, workshops, training, and collaborative engagement with researchers and research staff
Skills
- Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Biomedical Informatics, or a related field, and/or equivalent combination of education and experience
- Minimum 10 years of progressively responsible experience, including substantial experience leading technical strategy, architecture, and platform development initiatives and serving as a technical lead, principal engineer, or primary technical expert for a research program, center, or
- Expert-level experience designing and architecting research software, data-intensive applications, analytical platforms, scientific computing systems, and modern data architectures
- Expert-level proficiency in Python and SQL, with experience in one or more additional research computing or data science languages
- Advanced full-stack application development experience, including modern web frameworks, API design, relational databases, and secure deployment and DevOps practices
- Experience working with healthcare, clinical, public health, health services research, policy, claims, or other large-scale observational datasets
- Experience evaluating, prototyping, and implementing artificial intelligence technologies in research, analytical, or knowledge-intensive environments
- Expert knowledge of secure software development, data privacy, access controls, governance frameworks, and responsible stewardship of research data, including HIPAA-regulated and IRB-governed clinical and research data
- Strong understanding of data engineering, data modeling, metadata management, data governance, data visualization, and reproducible research practices
- Demonstrated ability to establish technical direction, architecture, standards, and implementation strategies in complex or highly ambiguous environments
- Experience serving as the primary technical lead, architect, or senior technical contributor supporting an academic, scientific, clinical, or research-focused program
- Experience developing researcher-facing software applications, analytical tools, self-service data capabilities, or AI-enabled research solutions
- Experience with relational database platforms, columnar data formats, and analytical technologies (e.g., PostgreSQL, MySQL, Parquet, DuckDB)
- Experience administering or supporting Linux-based research computing environments, containerized deployments, infrastructure automation, CI/CD workflows, automated testing, or Git-based collaborative development
Benefits
- The final salary and offer components are subject to additional approvals based on UC policy.
- Your placement within the salary range is dependent on a number of factors including your work experience and internal equity within this position classification at UCSF.
- For positions that are represented by a labor union, placement within the salary range will be guided by the rules in the collective bargaining agreement.
- To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html
Company Overview