Program Officer, AI Resources

In A Nutshell Location Hybrid San Francisco, CA, United States

Salary $220,000 - $300,000 / year

Job Type Full-time

Experience Level Mid-level

Deadline to apply October 30, 2026

We are hiring at least two founding Program Officers for AI Resources: generalists with technical judgment who will be the team lead’s right hands across everything the team does: operations, grantmaking, research, strategy, and partnerships. You will report to Lennart Heim, Director of AI Resources.

Responsibilities

• Do research on what the AI resources portfolio should look like and which actions to take now (thinking through potential compute crunches, counterparty risks, and market scenarios) and help shape the team’s strategy.
• Help figure out how to scale AI resources to grantees, within the Foundation itself, and for what this means for the future of philanthropy: how every part of AI resilience (biosecurity, model safety, cybersecurity, and more) can benefit from and be uplifted by AI.
• Conduct research that informs program strategy: where returns to AI resources are highest, where diminishing returns set in, what grantees actually demand, what it takes for organizations to absorb more AI resources, and whether providing AI resources directly creates more value than cash.
• Support grantmaking end to end (sourcing, diligence, and getting resources into grantees’ hands) including grant investigations.
• Help identify the projects and organizations that should exist in this space, and support finding or developing the people to build them.
• Work closely with the broader AI Resilience team on the wider set of issues across biosecurity, cybersecurity, model safety, and more, and find where AI Resources can support.

Additionally, we’re hiring for a person specialized on partnerships who will focus on:

• Explore and execute potential compute acquisitions, deals, and rentals across the portfolio, weighing trade-offs across cost, security, time-to-delivery, scale, and counterparty risk, and maintaining the acquisition portfolio.
• Design and execute the financing side with Foundation finance, legal, and tax: how arrangements get paid for and which structures fit which needs.
• Build and manage the partnership with OpenAI PBC (model access, tokens, and compute arrangements) and engage counterparties across the market, representing the Foundation credibly to senior executives at providers, AI companies, and financial institutions.

Skillset

• Are a doer with generalist range: high execution, comfortable with ambiguity and context-switching, and able to move between operations, grantmaking, research, and strategy without dropping quality.
• Follow frontier AI capabilities and risks closely enough to have independent judgment about them and can translate that judgment for grantees, providers, and internal stakeholders.
• Take the AGI trajectory seriously, including short timelines and the possibility of recursive self-improvement, and have a view on where AI is going: your own takes on how capabilities will develop, a model of the role AI systems will play in future worlds and how compute will power them, and a grasp of the team’s core hypothesis: that increasingly capable AI can be directed at the challenges it creates.
• Are fluent in the technical layers (data centers, compute, AI models, and infrastructure in general) with enough compute literacy to sanity-check a cluster or token request.
• Have deep familiarity with the AI resilience, safety, and security ecosystem, ideally with an existing network.
• Are AI-native: you use AI tools by default and look for ways to automate and compress routine work.
• Are deeply mission-aligned and excited to help ensure AGI benefits all of humanity.

It would be great if you also have

• Grantmaking, philanthropy, or research-funding experience.
• Industry experience striking deals on compute capacity, tokens, and more (you may have rented GPU clusters or even managed them), ideally with an existing network across compute providers, financiers, and AI companies.
• A technical background with deeper expertise somewhere along the AI stack (from semiconductors and compute infrastructure to AI development, deployment, and the surrounding tooling) ideally with exposure to model alignment, safety, or evaluations.

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