Lead partner performance measurement, attribution, and reporting; build dashboards and KPIs; drive operating cadences (forecasting, pipeline, business reviews); partner with Finance and Revenue Ops on targets and quota allocation; and lead cross-functional initiatives to automate and improve Partnerships effectiveness.

The Technical Program Manager will manage interdisciplinary programs for the Trustworthy AI team, facilitating partnerships, driving strategic projects, and synthesizing research for actionable insights.

Lead and develop a team of recruiters for Sales and GTM roles, optimizing processes for effective hiring and improving candidate experience.

The role involves building and maintaining systems for iterative development and deployment, focusing on a seamless developer experience in a large monorepo environment.

The role involves managing sourcing execution for suppliers, ensuring operational excellence, and collaborating across departments. Responsibilities include deal execution, analytics, and stakeholder communication.

Develop and execute external communications strategies for OpenAI research. Translate technical work into accessible narratives, manage research-focused media engagement, support research launches and publications, coordinate cross-functionally, and anticipate and mitigate reputational or scientific risks.

Lead growth strategy for ChatGPT's self-serve Business plan, optimizing user journeys and collaborating across teams to enhance value and conversion.

The role focuses on managing the delivery of data center projects, ensuring on-time completion, and coordinating with stakeholders and vendors. It involves overseeing project milestones, budgets, and risk management, along with maintaining relationships with commercial partners like Oracle.

Design and build backend infrastructure for OpenAI's monetization products, focusing on large-scale distributed systems and collaboration across teams. Responsibilities include developing APIs and ensuring high engineering standards.

Responsible for delivering technical enablement and adoption services for OpenAI's product suite, training customers on usage, and ensuring sustained product adoption and measurable business value.

The Power Architect develops energy-efficient design for AI chips, collaborates with teams to optimize performance, and drives innovations in power management.

This role involves architecting and implementing ML-driven ads ranking and recommendation systems, focusing on performance, privacy, and continuous improvement. The engineer collaborates with cross-functional teams to translate product goals into scalable systems.

Partner with research teams to define hiring priorities and execute strategic searches for top AI/ML researchers and research engineers. Proactively source, evaluate, and close highly specialized technical candidates, advising on leveling and compensation while collaborating with sourcing partners through complex searches.

Provide technical support and troubleshooting for complex customer issues, use scripting and OpenAI tools to automate processes, partner with engineering and product teams to resolve bugs, improve support systems, and scale operations while participating in on-call and weekend coverage.

Design and scale infrastructure for multimodal training at OpenAI, focusing on distributed data systems and collaborating with researchers.

Build and own autonomous, customer-facing systems to drive revenue and marketing efficiency while partnering with stakeholders for success metrics.

Embed with Product and Engineering to define success metrics, design measurement and experimentation frameworks, instrument and monitor launches, translate model-driven signals into decisions, and build repeatable decision loops to convert analysis into shipped changes.

Build and maintain Lead-to-Opportunity Salesforce solutions, integrations, and data enrichment workflows. Troubleshoot production lead capture/routing issues, document processes, and collaborate cross-functionally to support GTM pipeline creation and lifecycle engagement.

The role involves end-to-end development of backend systems for AI in finance, collaborating with various teams to implement solutions and improve models.

Co-design hardware for AI workloads, optimize ML platform code, develop system performance models, and collaborate with engineers and vendors to influence hardware design.