Lead the development of the infrastructure that could define how society governs increasingly powerful AI systems.
As AI systems become increasingly capable, one question is becoming unavoidable: how can powerful systems be independently scrutinized when the organizations involved cannot fully share what they know?
AI developers are protecting frontier models worth billions of dollars. Auditors, safety researchers, and regulators often rely on sensitive evaluation methods, proprietary benchmarks, and restricted datasets that cannot be publicly disclosed. Yet meaningful oversight depends on both sides being able to collaborate.
At OpenMined, we're building the privacy-preserving infrastructure that makes trustworthy oversight possible without requiring trust. Using privacy-enhancing technologies, secure computation, and distributed systems, we're creating the rails that allow AI developers, auditors, safety institutes, researchers, and regulators to run evaluations without exposing models, datasets, prompts, or proprietary methodologies.
Independent AI evaluation is still an emerging field, and many of the standards, systems, and operational models that will govern how frontier AI is assessed have yet to be established. As the TPM leading this effort, you'll help define them. Working with leading AI labs, AI safety institutes, researchers, and public institutions, you'll shape product strategy, drive ecosystem adoption, and help turn privacy-preserving evaluation from an emerging concept into critical infrastructure.
The challenges you'll tackle span distributed systems, cryptography, privacy-preserving computation, AI evaluation, and institutional trust. Success means expanding adoption among AI labs and evaluators, enabling increasingly sophisticated evaluation workflows, and delivering strategic integrations that demonstrate how independent oversight can work in practice.
If successful, the systems you help build could become part of the foundation that allows increasingly powerful AI models to be evaluated safely, independently, and credibly without requiring organizations to expose their most valuable assets. In a future where AI governance depends on trustworthy mechanisms for independent evaluation, your work will make those mechanisms possible.
Responsibilities
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Drive adoption of OpenMined’s privacy-preserving evaluation infrastructure across AI labs, safety organizations, governments, and research institutions. This includes developing strategic partnerships, identifying high-impact deployment opportunities, and helping establish OpenMined as a trusted voice in the emerging AI evaluation and governance ecosystem.
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Work closely with engineers and researchers to define the next generation of infrastructure required for privacy-preserving AI evaluations. You’ll help shape capabilities that enable increasingly sophisticated evaluation scenarios.
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Lead the delivery of high-profile strategic deployments with frontier AI organizations, ensuring that pilots and production integrations are executed efficiently and generate meaningful outcomes for both partners and the broader ecosystem.
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Translate emerging needs from AI labs, safety institutes, policymakers, and regulators into product strategy, ensuring our infrastructure evolves alongside advances in AI capabilities and governance requirements.
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Represent OpenMined externally through industry working groups, conferences, standards efforts, and policy discussions, helping shape how privacy-preserving evaluation and auditing infrastructure develops as a field.
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Define the product roadmap, success metrics, and execution priorities that enable OpenMined to become foundational infrastructure for independent AI evaluation and oversight.
Requirements
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Come from the AI auditing, AI safety, AI evaluation, or responsible AI ecosystem or adjacent field, whether as a researcher, auditor, AI developer, policy technologist, or product leader.
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Have 3+ years of product management experience building or scaling technical products, ideally for developers, researchers, data scientists, auditors, or other technical users.
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Have a strong technical foundation and can collaborate deeply with engineers to ship complex software. You should be able to reason about distributed systems, privacy technologies, AI infrastructure, and the practical trade-offs involved in building reliable technical products.
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Are hands-on with code and technical tooling. You do not need to be a full-time engineer, but you should be comfortable reading PRs, debugging product issues, prototyping ideas, and using technical judgment to help the team move faster.
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Have strong AI ecosystem fluency, including a grasp of model advances, agentic systems, evaluation infrastructure and full-stack AI architecture.
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Can bridge research and implementation, turning emerging technical capabilities into practical product directions. You are intellectually curious about areas like secure computation, privacy-preserving evaluation and AI auditing infrastructure.
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Are an exceptional communicator, both in writing and conversation. You can align distributed teams, create clarity from ambiguity, and build trust with engineers, researchers, policymakers, AI labs, auditors, and strategic partners.
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Are strong at relationship-building across diverse stakeholder groups. This role requires credibility with technical teams as well as the ability to work productively with institutions, policymakers, safety organizations, and external partners.
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Are mission-driven. You care deeply about how technology shapes society and are excited by OpenMined’s goal of unlocking the world’s non-public information while preserving privacy, security, and trust.
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You have great product taste, in this case a product that is tailored towards a mix of technical and policy users. You can distinguish good UX from bad UX in this space and you understand the technical and product tradeoffs well enough to make informed decisions about the design.
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You bring strong strategic planning skills and a pragmatic approach to execution. You know how to achieve milestones with focused, efficient effort; understand the tradeoffs involved in key decisions and shortcuts; and can identify the right expert input needed to make those decisions well.
Nice-to-Haves
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Experience as a data scientist or building products for data scientists, including familiarity with workflows in Colab, Jupyter, notebooks, datasets, and model evaluation tooling.
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Contributions to open-source projects, technical standards, governance frameworks, or research communities.
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Exposure to public policy, privacy, AI governance, technology regulation, or institutional risk management.
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Entrepreneurial or founder-like experience, especially in environments where you had to build both a product and an ecosystem from scratch.
