What are the responsibilities and job description for the Principal Research Software Engineer position at University of California - San Francisco?
Job Summary:
We are seeking a Principal Research Software Engineer to serve as the primary technical expert supporting a nationally recognized health policy research program.
Our program's active research collaborations span Harvard University, Mass General Brigham, Yale University, Penn State, the National Bureau of Economic Research (NBER), the Naval Postgraduate School (NPS), and public universities both within California and in other states, including UCLA, UC Davis, the University of Washington, the University of Texas, and the University of Florida. This position is responsible for ensuring that our data and technical platforms are usable, interoperable, and compliant across this entire range of environments - private research universities, public universities in and outside California, a major academic health system, a nonprofit economic research organization, and a federal Department of Defense institution - each with its own data governance, security, and regulatory regime, including federal information-security requirements on the NPS side.
- Having wide-ranging experience, applies advanced software engineering, data engineering, informatics, and artificial intelligence technologies to projects, up to and including the most complex, with multi-institutional scope and little or no precedent. Serves as the primary technical expert for a nationally recognized health policy research program whose findings directly inform federal, state, and local health policy. Is considered a subject matter expert on research software engineering, data systems, and AI-enabled research across the program and its collaborating institutions. Directs the selection of tools, methods, techniques, technologies, and evaluation criteria to obtain results. Internal and external contacts regularly pertain to multi-institutional plans and objectives.
- Directs the program's research technology portfolio, leading the development of research software, data platforms, and computational capabilities with multi-institutional impact that accelerate scientific discovery, enable innovative analyses, and generate publications and policy insights with impact beyond the University. Regularly leads projects of critical importance to the organization: federally funded, multi-site research initiatives in which the security, reliability, and reproducibility of software and data systems carry substantial consequences of success or failure, including regulatory compliance, continued federal funding, and the integrity of evidence used in national and state health policy decisions.
- Works closely with the Principal Investigator, research staff, and external collaborators to identify opportunities where technology can amplify research productivity, scientific discovery, and organizational impact. Establishes and evolves research technology strategy, technical standards, architecture principles, and foundational capabilities, formulating strategies and administering technical policies, processes, and resources that guide current and future research initiatives across the program and collaborating institutions. Has significant impact and influence on organizational policy and program development, including governance policies for the responsible use of artificial intelligence and regulated data.
- Exercises substantial independent judgment in determining technical strategy, architecture, tools, methodologies, partnerships, and implementation approaches. Serves as a trusted technical advisor on research software, data infrastructure, and artificial intelligence, helping researchers evaluate and responsibly adopt emerging technologies. Develops reusable software, data, and AI capabilities that support multiple research projects, collaborating institutions, and future scientific initiatives. The position requires a rare combination of expert-level software engineering, data architecture, artificial intelligence, and regulated health data expertise.
Department Summary:
The Philip R. Lee Institute for Health Policy Studies (PRL-IHPS) is an organized research unit within the School of Medicine (SOM). The primary purposes of the Institute are to advance knowledge of health services and health policies through basic and applied research; to contribute to the solution of health and social problems through the application of research findings to health policy issues at the national, state, and local levels.
% of time | Essential Function (Yes/No) |
Key Responsibilities (To be completed by Supervisor) |
| 55 | Yes | Research Software Engineering and Data Platforms 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. |
| 25 | Yes | AI Strategy and Enablement
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.
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| 15 | Yes | Research Technology Leadership and Strategy
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.
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| 5 | Yes | Knowledge Sharing, Open Science, and Community Impact
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.
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| 100% |
Required:
- 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.
Preferred:
- 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.
Required:
- 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.
Preferred:
- 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.
Equal Employment Opportunity: The University of California San Francisco is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.