Technical Program Manager, Model Deployment & Capacity
About this role
Managing chat capacity forecasting, allocation, and headroom planning forms the core of daily operations for this Technical Program Manager at OpenAI. The individual shapes the operating system for model deployment by connecting demand forecasting and capacity allocation directly with model readiness, rollout planning, launch coordination, and post-deployment learning. Operating at the intersection of product demand, model deployment, inference, research, fleet, and capacity, the team translates shifting model requirements into clear capacity decisions and scalable launches.
OpenAI builds high-impact systems like ChatGPT, API platforms, and enterprise capabilities that must perform reliably at a global scale. This role exists to bring structure to constrained-capacity decisions, improve prioritization tooling, and help new models reach users safely. Candidates who thrive here typically possess deep technical understanding, sound judgment during ambiguous situations, and the ability to execute across product, research, infrastructure, and operations teams without direct authority.
What you will do
- Manage cross-functional programs focused on Chat capacity forecasting, allocation, headroom planning, and constrained-capacity operations.
- Develop durable intake, prioritization, and decision mechanisms linking product demand and model requirements to available serving capacity.
- Collaborate with product, research, inference, fleet, and capacity teams to formulate scenarios, evaluate tradeoffs, and drive timely allocation decisions.
- Oversee model deployment readiness and rollout planning, encompassing serving-capacity allocation, launch sequencing, validation, and operational handoffs.
- Define clear readiness gates, risk reviews, rollback criteria, and escalation paths for all model deployments.
- Coordinate launches through deployment and post-launch learning to transition recurring manual workflows into scalable tooling.
- Establish and operationalize metrics covering forecast accuracy, capacity utilization, deployment velocity, reliability, latency, quality, and user impact.
- Produce concise, decision-ready communications that clarify dependencies, risks, capacity constraints, and launch choices for technical and product leaders.
What you need
- Demonstrated experience leading complex technical programs in infrastructure, distributed systems, capacity planning, model serving, or large-scale deployment environments.
- Ability to reason credibly about demand, supply, headroom, reliability, latency, and quality tradeoffs to build executable plans.
- Track record of building operating mechanisms or tooling that replace manual workflows with scalable systems and clear ownership.
- Effectiveness operating in high-ambiguity, constrained environments where shifting priorities require explicit tradeoffs.
- Capacity to build alignment across research, engineering, product, finance, capacity planning, and operations without relying on direct authority.
- Proficiency in using metrics to guide decisions, identify bottlenecks, and demonstrate measurable improvements in throughput, predictability, or reliability.
Benefits
- Offers Equity
- Relocation assistance to new employees
Skills and tech stack
Questions candidates ask
Where is the role located and what is the remote policy?
This role is based in San Francisco, CA. The company uses a hybrid work model of 3 days in the office per week.
What is the compensation range for this position?
The salary ranges from $207K to $445K and includes offers of equity. Relocation assistance is also offered to new employees.
What kind of team will I be working with?
You will work within the ChatGPT infrastructure team at the intersection of product demand, model deployment, inference, research, fleet, and capacity. The position requires partnering with cross-functional teams across research, post-training, inference, and product.