Founded by Priscilla Chan and Mark Zuckerberg in 2015, the Chan Zuckerberg Initiative (CZI) is a new kind of philanthropy that’s leveraging technology to help solve some of society’s toughest challenges – from eradicating disease, to improving education. Across our core initiatives of Science and Education, we’re pairing engineering with grantmaking, impact investing, policy work, and advocacy, to progress in our mission of building an inclusive, just and healthy future for everyone.
We believe we can help build a future for everyone.
- We aim to be daring, but humble: We look for bold ideas — regardless of structure and stage — and help them scale by pairing engineers with subject matter experts to build tools that accelerate the pace of social progress.
- We want to learn fast, but build for the long-term: We want to iterate fast and help bring new solutions to the table, but we also realize that important breakthroughs often take decades, or even centuries.
- Stay close to the real problems: We engage directly in the communities we serve because no one understands our society’s challenges like those who live them every day.
Our success is dependent on building teams that include people from different backgrounds and experiences who can challenge each other's assumptions with fresh perspectives. To that end, we look for a diverse pool of applicants including those from historically marginalized groups — women, people with disabilities, people of color, formerly incarcerated people, people who are lesbian, gay, bisexual, transgender, and/or gender nonconforming, first and second generation immigrants, veterans, and people from different socioeconomic backgrounds.
By pairing engineers with leaders in our science teams, we can bring technology to the table in new ways to help drive solutions. We are uniquely positioned to design, build, and scale software systems to help scientists better address the myriad challenges they face. Our technology team is already helping scientists around the world visualize and interpret large scale imaging datasets, mine literature to keep abreast of what is happening in their fields, and develop the methods for a comprehensive reference of all cells in the human body.
As our Director of Engineering, you will lay the foundation for our Science engineering team focused on creating technology products to support our mission in Science. In this position, you will work with colleagues from a variety of different roles across the company as well as external partners, including scientists, researchers, and policy makers. You will work with these stakeholders to conceptualize and define engineering projects and goals, and you will build and deploy software to accomplish these goals. Example projects which are likely in the scope of this team: Meta.org, IDseq, cellxgene, and napari. The position is full-time and based in our office in Redwood City.
- Collaborate with leaders in Science to identify high impact engineering projects and provide technical evaluation and recommendations.
- Map out engineering resource needs and help to establish engineering culture and best practices.
- Recruit engineering team members of all levels.
- Manage a multi-level team (manager of managers) and lead a growing engineering team with a bias towards nimble, self-managing project teams. The team comprises a wide range of skills and seniority levels, and will require the management of software managers with a variety of professional backgrounds.
- Ensure the team’s ability to collect and synthesize project requirements, create effective project roadmaps, and ship high quality products.
- Actively participate in the Scientific and OSS communities surrounding CZI Science.
- Proven ability to assemble and lead multiple engineering teams who ship products
- 10+ years of relevant software engineering experience
- 5+ years of experience as an engineering manager, particularly in a high-growth environment
- Experience in building diverse, inclusive and equitable teams and working environments
- Experience in one or more of the following areas is a plus: machine learning, recommendation systems, pattern recognition, large-scale data mining, artificial intelligence, filesystems, database systems, server architectures, and distributed systems