Open Source Research Software Engineer: Agentic AI (0652) Job #88097 - BIDS

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Since its launch in 2013, BIDS has been dedicated to accelerating data-driven discovery by fostering an environment of open inquiry and cross-disciplinary collaboration. We have successfully broken down traditional academic silos, uniting domain experts from the life, physical, and social sciences, as well as the arts and humanities, with methodological leaders in computer science, statistics, and applied mathematics.

BIDS is expertly positioned as the central hub for advancing interdisciplinary data science research, academic training, and software development within the UC Berkeley College of Computing, Data Science, and Society. BIDS houses UC Berkeley's Open Source Program Office and champions open science, open source software, and open scholarship. We serve as a discipline-agnostic space to rally Berkeley's unique ecosystem, driving forward innovative collaborations that explore the profound impacts of Artificial Intelligence on both science and society.

UC Berkeley and UCSF have launched a joint program called the Bakar Computational Biomedicine Initiative to develop the frontier of AI and biomedicine, tremendously accelerating advances in clinical care. The new partnership brings together world-class faculty expertise in computing, AI, statistics, biology and medicine, to speed discovery in everything from disease prevention, to early-detection and new therapeutics in healthcare.

As part of this effort, at BIDS our team of open source research software engineers (OS-RSEs), product managers, and computational postdoctoral researchers will build the BioJupyter platform. Based on the widely adopted architecture of Project Jupyter and developed as part of the existing Jupyter ecosystem, with advancements and contributions to existing Jupyter components as well as the development of new tools, BioJupyter will bring next-generation features to facilitate collaboration in data-intensive, AI-powered biomedical research. These will include, but not be limited to, advances in core Jupyter components for collaboration and data sharing across deployments in separate hosting environments (ranging from local clusters and HPC facilities to the cloud), integration of AI agents and tools into the research workflow, sharing of intermediate results, code and pre-publication outputs with fine-grained access control, and fluid integration of these Jupyter deployments alongside existing research tools and environments that are independent of Jupyter.

OS-RSEs bring software engineering expertise and open source development practices to interdisciplinary projects. They play the role of an "expert collaborator" who solves problems at the intersection of research, software, and modern computing infrastructure. They regularly investigate -- and propose solutions to -- open-ended, unstructured challenges that arise from the computational needs of researchers. They scope, and deliver on technical requirements that require an in-depth evaluation of cutting edge data science and AI applications. They are integral members of a diverse team, co-creating the BioJupyter platform to solve real world challenges in the biomedical sciences.

OS-RSEs work closely with senior researchers, industry partners, and stakeholders across global scientific open source projects in the Jupyter ecosystem, as well as those of the computational tools used by our researchers today, including Scientific Python, R, and beyond. They create, improve, and maintain parts of the open source software ecosystem that underpins global innovation in data science and AI. They advocate for open science and open scholarship best practices, and meet national and global standards around responsible and ethical uses of technology. They showcase research outputs and software tools to the research community and industry partners through presentations, research papers, blog posts, interactive data visualizations, and open source software packages.

The OS-RSE working on BioJupyter's product design and development focuses on the Research Experience (RX): the frontend, backend, and agent interactions through which scientists scope and delegate work, leverage AI, and share data, tools, and knowledge publicly and privately. They define these interactions based on deep collaborations with real-world researchers across scientific domains and institutions who have diverse expertise using agentic and computational workflows. They iterate quickly, building prototypes and collecting feedback from biomedical researchers in person and through private or public asynchronous pathways such as GitHub issues and discussions. They embed joy in every stage of the RX: designing systems that deliver robust, trustworthy outputs with little to no extra effort from the scientist themselves.

The First Review Date for this job is: August 24, 2026 - Open Until Filled

The next review date for this job is September 7, 2026.

40% Applies advanced software concepts to plan, design, develop, modify, debug, deploy, and evaluate highly complex interface, software, and/or infrastructure solutions in interdisciplinary research collaborations.

20% Contributes to and supports the maintenance and sustainability of 1-4 projects within the scientific open source ecosystem. Maintenance can include issue triage, code and documentation review, contributing new features, mentoring new contributors, continuous integration testing, and release management.

10% Develops project plans as part of an interdisciplinary team, delivers allocated tasks, and communicates progress regularly.

5% Analyzes existing highly complex open source software or works to formulate logic and devises algorithms for new modular and composable software systems. Understands and applies industry practices, open source community standards, and department policies and procedures in depth.

5% Enables collaborators to design, implement, reproduce, and extend highly complex data analyses to address real-world research problems, including accessing data from varied multi-modal processing pipelines, working directly with domain scientists and open source communities as appropriate.

5% Stays up to date on applicable research and software engineering standards, including applications of agentic AI for science (new models and tools, agentic architectures, and evaluation methods), and security and accessibility practices. Implements cutting-edge practices into software and protocol standards, meeting UC Berkeley-specific policy requirements and national and international standards as applicable.

5% Prepares and approves or obtains approval for user and developer documentation. Initiates and oversees changes in development, maintenance and system standards. Sets the technical requirements for software specifications, engaging across open source communities as appropriate. Communicates technical requirements to interdisciplinary experts and trainees with varied technical expertise.

5% Serves as technical lead for one or two software development projects of moderate to broad scope. Meets with interdisciplinary project teams and provides regular updates on progress.

5% Advances the work of the UC Berkeley Open Source Program Office (OSPO) by demonstrating the value and impact of open source practices. Delivers trainings and provides technical and community mentorship to members of the UC-wide OSPO network. Participates actively in monthly meetings and workshops.

• Advanced programming skills, including Python expertise.
• Demonstrated fluency using agentic AI and large language model (LLM) coding agents (such as Claude and/or Codex) for software engineering.
• Experience building software, tooling, or infrastructure for agentic AI / LLM systems such as agent frameworks, tool and skill integrations, or evaluation harnesses.
• Demonstrated software development and maintenance skills: version control with git, testing, continuous integration and/or continuous deployment with GitHub Actions or similar. Advanced knowledge of secure software development.
• Experience participating in multi-stakeholder open source communities: distributed decision making, navigating uncertainty, building consensus, coordinating paid and volunteer contributors, mentoring new members.
• Experience reviewing code through open discussion and iterations on GitHub. Demonstrated track record using issues and pull requests (or similar) for transparent and distributed project management.
• Experience structuring and analyzing complex and multi-modal datasets, ideally following and contributing back to open standards.
• A curious mindset and appetite for navigating complexity and uncertainty. A track record of scoping and delivering on requirements from interdisciplinary teams of domain experts and trainees with varied technical expertise.
• Advanced skills associated with software specification, design, modification, implementation and deployment of large-scale scope.
• Demonstrated ability to understand functional needs and how systems can support those needs, particularly in the context of leveraging existing functionality in scientific open source libraries.
• Advanced experience with planning for real-world deployment and creation of feedback mechanisms across an interdisciplinary team.
• Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and at academic and industry conferences.
• Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines.
• Demonstrated complex problem-solving skills.
• Bachelor's degree in a related area and/or equivalent experience/training.

• Proven track record building tools that are used by academic research teams to conduct cutting-edge innovation in the life sciences, physical sciences (astronomy, physics, chemistry), and geosciences, and/or the social sciences, humanities, and public health.
• Experience conducting biomedical research in academia or industry.
• Experience deploying and/or contributing to JupyterAI or related open source projects.
• Excellent project leadership and management skills.

For information on the comprehensive benefits package offered by the University, please visit the University of California's website.

Under California law, the University of California, Berkeley is required to provide a reasonable estimate of the compensation range for this role and should not offer a salary outside of the range posted in this job announcement. This range takes into account the wide range of factors that are considered in making compensation decisions including but not limited to experience, skills, know