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The Solutions Engineer will engage with Enterprise customers to optimize their experience with OpenAI products, offering technical guidance and support throughout the pre-sales process, ensuring successful implementation and maximizing business value.

The Performance Modeling Engineer will develop tools for evaluating AI system performance, analyze system behavior, and assist in architecture decisions, collaborating with senior engineers.

Build backend services, APIs, and cloud infrastructure to extend OpenAI's API into cloud-native environments (starting with AWS). Develop cloud-contained products, cloud-hosted Codex experiences, stateful agentic runtime abstractions, and SDK/auth integrations. Partner with internal teams and external cloud partners to deliver reliable, scalable, and observable production systems while shaping the technical direction of a growing team.

The role involves building infrastructure for AI agent execution environments, ensuring system reliability and optimizing performance at scale.

Lead procurement operations for assigned hardware business units from intake through PO creation, supplier coordination, receiving readiness, and invoice handoffs. Redesign workflows, build automations and AI-enabled processes, enforce fiscal controls and audit readiness, drive metrics improvements, and serve as primary operational escalation for hardware procurement activity.

Design and implement firmware and drivers for AI hardware components, develop functional models, and debug issues in embedded systems.

The Solutions Engineer ensures Digital Native customers gain business value from OpenAI products by providing technical support, creating demos, guiding architecture decisions, and fostering long-term relationships while addressing customer security and compliance inquiries.

Monitor and forecast emerging AI misuse and strategic threats via mixed qualitative and quantitative methods. Build and maintain harm taxonomies, risk registers, and early-warning metrics. Translate findings into prioritized mitigation proposals, dashboards, and executive briefings. Run scenario analyses, tabletop exercises, and benchmark risk posture to inform product and safety decisions.

The Performance Modeling Engineer will develop modeling tools to analyze AI system performance, collaborating on architectural tradeoffs and validating models against real data.

The role involves leading the architecture and development of identity infrastructure, enhancing security, reliability, and operational maturity across cloud platforms and internal systems.