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The Technical Program Manager will oversee critical programs in compute infrastructure, facilitating coordination among research and engineering teams, ensuring efficient resource allocation and management.

This role involves developing infrastructure that supports AI product development, enhancing developer productivity, managing cloud operations, and ensuring scalable identity solutions while collaborating across teams.

As a Technical Program Manager, you will lead end-to-end program management for AI product launches, coordinating between research, engineering, and product teams, ensuring reliable and timely launches while managing dependencies and stakeholder expectations.

Build and enhance iOS applications using cutting-edge technology, collaborating with various teams to develop user-friendly mobile experiences and optimize app performance.

Manage node lifecycle for AI infrastructure, optimize health and capacity of hardware, and mentor engineers while driving technical strategy.

Own and operate Kubernetes control plane components, scale the Kubernetes scheduler, build core cluster services, collaborate with teams, and lead incident response.

Manage high-volume compute and infrastructure contracting from intake through signature. Own and administer the CLM system, design intake/workflows, build templates and playbooks, run reporting and SLAs, manage post-signature obligations, streamline processes, and deploy LLM/AI tooling to scale contracting efficiency across datacenter, hardware, construction, and network vendor agreements.

Lead and coordinate cross-team roadmap for shared Apps platform: sequence work, manage dependencies, drive platform adoption, reduce duplication, establish operating rhythms, produce program documentation, surface and resolve technical blockers, and facilitate cross-org decision making to increase developer velocity and product shipping reliability.

As part of the Safeguards Data Science team, you will analyze user behavior, define success metrics, and foster a data-driven culture to improve AI safety.

Lead and grow an engineering team to build enterprise-grade platform features for deploying Claude at scale. Own planning, delivery, incident response, and cross-functional partnership with product, sales, security, and legal to meet enterprise security, compliance, and operational requirements.