Tokens-as-a-Service (Taas) Software Engineer

About the Role We are seeking a Tokens-as-a-Service (TaaS) Engineer to help build the systems that convert large-scale infrastructure capacity into measurable, reliable token throughput for OpenAI workloads. In this role, you will work across performance benchmarking, tokenomics, model porting, infrastructure integration, systems tooling, and operational monitoring. You will help connect partner and first-party compute environments into OpenAI’s infrastructure stack, ensuring GPU capacity can be onboarded, measured, monitored, and optimized against real workload outcomes. Key Responsibilities Develop systems and tooling to measure, monitor, and improve token throughput across first-party and partner-owned compute environments. Support performance benchmarking, tokenomics analysis, and model porting across heterogeneous infrastructure environments. Build tooling to integrate external or partner infrastructure into OpenAI’s internal compute, observability, and workload management systems. Develop and monitor operational metrics including billing, usage, SLAs, utilization, reliability, and throughput. Identify bottlenecks across hardware, networking, software, and workload enablement that prevent capacity from becoming productive tokens. Partner with compute, infrastructure, networking, finance, and operations teams to translate raw capacity into usable workload-serving capacity. Build dashboards, automation, and reporting systems that provide clear visibility into TaaS capacity, performance, and business outcomes. Qualifications Strong software engineering background with experience building systems, tooling, automation, or infrastructure platforms. Experience working across compute infrastructure, distributed systems, performance engineering, or production operations. Ability to reason about token throughput, utilization, benchmarking, infrastructure efficiency, and workload performance. Comfortable integrating external systems or partner environments into internal infrastructure stacks. Strong analytical and debugging skills across hardware, networking, software, and operational domains. Preferred Skills Experience with GPU clusters, AI infrastructure, performance benchmarking, or workload optimization. Familiarity with model porting, inference/training workloads, token economics, or compute efficiency analysis. Experience building monitoring systems for billing, usage, SLAs, utilization, or infrastructure reliability. Background in systems engineering, infrastructure software, observability, distributed systems, or platform engineering. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. 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