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Lead the Large Enterprise AI Deployment Engineering team across EMEA to drive GenAI use cases into production. Manage customer technical journeys, align engineering and product roadmaps, mentor ADEs, and serve as primary technical escalation and industry thought leader.

Lead onsite IT operations for the Dublin office and coordinate EMEA regional IT support. Provide frontline support, onboarding/offboarding, AV and event readiness, vendor and inventory management, workplace technology for office builds, executive/white-glove support, and drive documentation, workflows, and automation to scale support across offices and time zones.

Manage design and implementation planning for ML acceleration chip hardware. Lead scheduling with strategic partners/vendors, coordinate internal resources, and drive cross-functional delivery from concept through data-center deployment.

Lead and scale the Statsig product engineering organization to deliver experimentation, feature rollout, dynamic configuration, and analytics platform capabilities. Define multi-year strategy, establish operating model and ownership, guide technical direction across frontend/backend/SDK/data/infrastructure, partner cross-functionally, balance adoption with reliability and safety, and build senior leadership bench to integrate Statsig as core product infrastructure at OpenAI.

Partner with strategic startup customers to prototype, build, and scale generative AI applications on the OpenAI API. Provide technical guidance, experiment with prototypes, synthesize product/model feedback, publish best practices, and build relationships across the startup ecosystem to accelerate customer impact.

Design, build, and operate reliable, scalable backend services and platform capabilities for monetization (pricing, billing, ads, payments). Own architecture, integrations, correctness, observability, and operational excellence. Lead cross-functional technical projects, write RFCs, mentor engineers, and deliver reusable developer tools and data products for product, finance, and GTM teams.

The role involves developing and scaling Codex for enterprise use, focusing on product evolution, system reliability, and customer engagement. Responsibilities include building secure systems, leading real-world deployments, and creating enterprise capabilities for operational improvements.

Develop and enhance software tools for hardware engineers, including compilers, simulation, and automation systems, while collaborating with design teams to improve hardware workflows.

As a Data Scientist on Codex, you will enhance AI developer tools by defining developer productivity, running experiments, and analyzing user metrics to guide product direction.

Design and debug software for embedded devices, working closely with hardware teams to optimize performance and deliver reliable systems.