Incubated Founder
Convergent Research, Palo Alto, CA, Remote
Research DevelopmentNot Required RequiredExecutive Director
Convergent Research, Palo Alto, CA, Remote
Advancements in AI bring both opportunities and serious risks. [ Atlas Computing](https://atlascomputing.org/) takes on society-scale AI risks that no existing institution is built to address — we design the intervention, validate it with domain experts and funders, then recruit and empower the specialist who will own it. You can think of us as: * A tiger team that identifies, scopes, and launches interventions that aren't a good fit for existing organizations * A design studio developing and staffing product requirements docs for coordination and market failures * A think tank combined with whatever their analog of "tech transfer" would be.
Some of the most important problems in catastrophic AI risk need owners: leaders who identify an overlooked, high-impact, and tractable problem; develop effective interventions; and ultimately take personal responsibility for bringing those interventions into the world. That’s why Atlas Computing is launching a selective program for people with deep domain expertise and the drive to address the most important risks facing society from growing AI capabilities. Founders will take one problem from a rough direction to a fundable plan: sharpening a concrete intervention, pressure-testing it against the field, building the relationships and founding team to execute it, and leaving with a grant proposal and the backing to pursue it. Our job is to lower the barriers to entry — both the cost of leaving your current career path and the risk that a good idea never gets off the ground — and to meaningfully raise the odds that the effort you launch succeeds. Founders will have between six months and two years to research a problem and develop a pitch, but we hold that loosely — a Founder is done when their effort is ready to stand on its own, not when a calendar says so. The goal is for Founders to develop an ambitious plan as quickly as possible (early graduations welcome), complete with conditionally committed users/stakeholders, an excellent founding team, expert advisors, and organizational plans like milestones — completion consists of pitching funders like Coefficient Giving and launching with an initial grant of around $10 million.
While future cohorts will tackle other neglected topics in navigating transformative AI, the first cohort focuses on securing AI infrastructure. This includes keeping the frontier AI systems out of the hands of actors who would steal, poison, or misuse them. The more powerful AI gets, the more critical it is to have strong guardrails, authorization systems, and safety mechanisms around it. However, most people working on catastrophic AI risk don’t have the necessary infosecurity experience to address these problems. We expect transformative AI will need to be secured against threat actors like nation-states, terrorists, insider threats, and even misaligned AIs themselves — actors who may have enormous resources, intentions to harm large numbers of people, or significant legitimate access. These may be the hardest, highest-stakes security problems you ever work on, and you'll be one of a very small pool of people qualified to work on them.
Examples of problems we're looking for owners on include: * **Securing AI from exfiltration:** protecting model weights and algorithms from theft. * **Securing AI integrity:** protecting models from tampering via data poisoning or other attacks. * **Enabling verification of AI datacenter properties:** demonstrations that would allow verifiable attestations that a data center is being used for inference or alignment research, rather than training. * Adjacent problems in AI infrastructure security (e.g., disconnected model safety, secure compute verification, protocols for using compromised AI, detecting and responding to rogue deployments) may also be in scope where they bear on keeping frontier models secure.
You can read a series of one-pagers about these problems [here](https://www.heronsec.ai/post/the-ai-infrastructure-security-shortlist).
By the end of the program, a successful Founder has: * Sharpened a rough direction into a concrete intervention, with attestations from domain experts that it's plausible and from decision-makers that it would change their behavior; * Built the relationships and founding team needed to execute it; and * Produced a grant proposal in partnership with an interested donor we’ll introduce. Joining the incubator does not guarantee funding for your project, but the goal of the program is to develop plans funders are excited to scale. If there's not a mutually satisfactory project to scale up, we'll support you in finding your next role.
Outcomes we'd be excited about: * You become the founder and/or directly responsible individual (DRI) of an object-level intervention. * You become a grantmaker or “[general manager](https://nanransohoff.substack.com/p/there-should-be-general-managers)” of grantmakers directing serious capital across this field * You become the advisor, mentor, and recruiter for the next wave of AI risk founders in this field.
We're not looking to maximize follow-on funding — we're looking for people the field builds around.
Atlas is also hiring [Field Strategists](https://jobs.lever.co/convergentresearch/aa2d1b42-e929-4c61-b582-d094c7b515f7), and we're running both searches at once, with separate applications. The two roles are complementary. * Field Strategists map a field’s incentives and bottlenecks, identify points of leverage, and de-risk high-impact interventions across an ecosystem. Their goal is to scope promising solutions clearly enough to pitch them, identify and recruit the right founders to own them, and support the handoff from strategy to execution. The field strategist holds an ongoing position at Atlas, building the skills and praxis for this approach for multiple efforts simultaneously and in series. * Founders take a single object-level project and iterate a rough idea into a fundable, executable plan. Founders will learn and practice field strategy for one specific problem, which will become a project they will remain responsible for and transition out of Atlas.
Upon joining Atlas, you're not locked in: a Founder who realizes their strength is ecosystem strategy can switch tracks, and vice versa.
You have one of the following backgrounds, or similar: * Experience working on cybersecurity in a national security context (especially building SL5 facilities, intelligence, or offensive security). * Experience in ML security research (tamper resistance, backdoors, password locking). * Experience in a relevant industry context — e.g., at a frontier AI lab, or in security at a hyperscaler, hardware company, or government contractor. * Exceptional capability in a relevant area — e.g., academic security research, security entrepreneurship, developing security standards, or AI hardware or firmware. You break down ambiguous problems into clear next steps, and don't get overwhelmed when you lack guidance. You can clearly articulate your plans, verbally and in writing, to coordinate and motivate others.
A practice of reviewing the state-of-the-art after having an idea, coupled with an urge to prototype, test, and iterate. Experience coordinating and aligning stakeholders to work toward a common goal. Strong analytical, problem-solving, and communication skills. Comfort with uncertainty and interest in shaping our culture, as we're still a very small organization. A strong compulsion to do something about AI risk — you understand what it would mean to be responsible for mitigating a particular risk from AI, and you want it anyway (because no one else is). The ability and inclination to do this work (to some extent) without Atlas, but you believe the program’s network, expertise, and institutional support would substantially decrease the difficulty, increase your odds of success, and/or scale your enjoyment while doing it.
Have a habit of doing non-technical coordination work despite a technical background. Have thought deeply about existential risk and made contributions to reducing it. Have led or started an organization, or managed people. Have already worked on related AI security problems, and have ideas you're ready to pursue. Have deep networks in cybersecurity or the AI safety community. Are great at getting people to tell you things they probably shouldn't have, getting into conversations with incredibly busy people, or coming up with creative ideas to align incentives. Have work authorization in the US.
Already have the answer to the problem you want to solve, and want funding more than a thought partner. Want a stable, well-scoped role with a clear roadmap handed to you. Are drawn to AI risk in the abstract but don't want to own a single specific, concrete problem. (If you'd be happy owning an area, [Field Strategist](https://jobs.lever.co/convergentresearch/aa2d1b42-e929-4c61-b582-d094c7b515f7) might be right for you...)
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
New types of organization are needed to accelerate scientific progress. Academic research groups and startup companies are essential to science and technology development. But there are some projects they just aren’t suited for. A university astronomy lab couldn’t have launched the Hubble Space Telescope on its own, nor would a venture-backed startup have built the Large Hadron Collider at CERN. Hubble and CERN illustrate a common pattern in science: a need for projects that are bigger than an academic lab can undertake, more coordinated than a loose consortium or themed department, and not directly profitable enough to be a venture-backed startup or industrial R&D project. Focused Research Organizations (FROs) are a new type of scientific institution designed to fill this gap.
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