Principal Research Software Engineer

UCSF•San Francisco, CA

12h

About The Position

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.

Requirements

Expert-level software engineering expertise.
Expert-level data architecture expertise.
Expert-level artificial intelligence expertise.
Expert-level regulated health data expertise.
Wide-ranging experience applying advanced software engineering, data engineering, informatics, and artificial intelligence technologies to complex projects.
Experience with multi-institutional scope and projects with little or no precedent.
Experience with diverse data governance, security, and regulatory regimes, including federal information-security requirements.
Experience developing reusable software, data, and AI capabilities.

Responsibilities

Serve as the primary technical expert supporting a nationally recognized health policy research program.
Ensure data and technical platforms are usable, interoperable, and compliant across multiple collaborating institutions with diverse data governance, security, and regulatory regimes.
Apply advanced software engineering, data engineering, informatics, and artificial intelligence technologies to complex, multi-institutional projects with little or no precedent.
Serve as a subject matter expert on research software engineering, data systems, and AI-enabled research.
Direct the selection of tools, methods, techniques, technologies, and evaluation criteria for research projects.
Direct the program’s research technology portfolio, leading the development of research software, data platforms, and computational capabilities.
Lead projects of critical importance, including federally funded, multi-site research initiatives where software and data system integrity are crucial.
Work closely with the Principal Investigator, research staff, and external collaborators to identify technology opportunities.
Establish and evolve research technology strategy, technical standards, architecture principles, and foundational capabilities.
Formulate strategies and administer technical policies, processes, and resources.
Influence organizational policy and program development, including governance policies for AI and regulated data.
Exercise independent judgment in determining technical strategy, architecture, tools, methodologies, partnerships, and implementation approaches.
Serve as a trusted technical advisor on research software, data infrastructure, and artificial intelligence.
Develop reusable software, data, and AI capabilities that support multiple research projects and collaborating institutions.