Store Officer in United States

About the Team The B2B Marketing team contributes to OpenAI's broader mission of ensuring responsible and widespread adoption of artificial intelligence. We are responsible for developing and executing strategies that drive awareness, engagement, and usage for OpenAI's products and platform. We take a data-driven approach to understand our customers' needs and challenges, ensuring that their voices are reflected in product development and messaging. We then partner closely with Product, Engineering, Growth, Sales, Research, Comms, and Design teams to create a cohesive customer experience across all our channels. About the Role We're looking for an enterprise Product Marketing Manager to own the administrator and governance experience across ChatGPT Work and Codex. IT administrators, security teams, and deployment owners are often the difference between an AI product being available and an organization actually putting it to work. This role will define how OpenAI earns the trust of the people responsible for approving, deploying, managing, and expanding AI inside their organizations. You will translate a fast-moving set of enterprise capabilities into a clear, practical story covering setup, access, controls, governance, security, usage, and value. You will own the administrator audience as a dedicated product marketing discipline, partnering closely with Product, Security, Sales, Customer Success, Growth, Customer Education, and other Marketing teams. Your job is not simply to announce new features. It is to help administrators understand what has changed, what they can control, how to deploy responsibly, and why expanding access is the right decision for their organization. In this role, you will: Own the IT administrator and governance audience: Build a deep understanding of the needs, decisions, objections, and workflows of workspace administrators, IT leaders, security teams, and enterprise deployment owners. Define the enterprise administration and governance s

About the Team The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models. Our work spans system software, networking, platform architecture, fleet-level monitoring, and performance optimization. About the Role We’re hiring an SW Engineer to enable production workloads and end-to-end testing on new platforms. This role will include creating new test harnesses and platform stress benchmarks, porting existing inference and training workloads to new, sometimes early-access, systems/hardware, analyzing performance and bottlenecks, and characterizing the end-to-end behavior of new systems (compute, comms, storage, control plane, and failure modes). Key Responsibilities Port and validate key inference and training workloads on new platforms/SKUs as they arrive; drive correctness, performance, and stability to an internal readiness bar. Build a suite of benchmarks and stress tests that capture real E2E behavior of our workloads by exercising all aspects of a system, including CPU, GPU, memory subsystem, frontend, scale-up, and scale-out networking (including WAN traffic, NVlink and RDMA collectives), storage, thermals, and any other relevant parts. Deep-dive performance on distributed training/inference: Collective performance and tuning (across NCCL/RCCL and internal libraries) Overlap of compute/communication, kernel-level bottlenecks, memory bandwidth and scheduling effects Create repeatable test harnesses that run in CI / lab environments and produce actionable outputs (pass/fail, performance score, regression detection). Partner with systems + fleet bring-up engineers to ensure the platform is not only stable and performant, but also operationally usable and scalable (containerization, K8s integration, telemetry hooks, failure triage loops). Work cross-functionally with vendors and internal stakeholders by producing