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

at OpenAI
USD 293,000-385,000 per year
MIDDLE
✅ Hybrid
✅ Relocation

Tech Stack

AI @ 3 Debugging @ 6 Distributed Systems @ 3 GPU @ 3 Networking @ 6 Observability

Details

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.

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.

Requirements

  • 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.

Benefits

  • Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
  • Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
  • 401(k) retirement plan with employer match
  • Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
  • Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
  • 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
  • Mental health and wellness support
  • Employer-paid basic life and disability coverage
  • Annual learning and development stipend to fuel your professional growth
  • Daily meals in our offices, and meal delivery credits as eligible
  • Relocation support for eligible employees
  • Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

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