OpenAI

Technical Program Manager, Model Deployment & Capacity

OpenAI$150K — $180K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in technical program management, especially in infrastructure or distributed systems.
  • Demonstrated ability to lead complex programs related to capacity planning and model deployment.
  • Strong understanding of forecasting demand, supply allocation, and operational metrics.
  • Experience in establishing scalable operating mechanisms or tooling in fast-paced environments.
  • Proven ability to communicate effectively with diverse cross-functional teams.

Responsibilities

  • Own cross-functional programs for Chat capacity management and model deployment.
  • Build frameworks for prioritization that connect product demands to capacity availability.
  • Collaborate with product and engineering teams to drive allocation decisions based on tradeoffs.
  • Lead readiness and rollout planning for model deployments, ensuring clear roles and timelines.
  • Establish frameworks to assess readiness, including risk reviews and rollback criteria.
  • Coordinate launches and drive continuous improvement through post-launch assessments.
  • Define metrics for performance monitoring across deployment and operational success.

Benefits

  • Hybrid work model with 3 days in the office per week.
  • Relocation assistance for new employees.
  • Opportunities to work at the forefront of AI technology.
  • Collaborative environment focused on innovation and responsible AI access.
  • Engagement in a mission-driven company aiming to solve global problems.
Full Job Description
About the Role

We are seeking a Technical Program Manager to lead the operating system for Chat capacity and model deployment. You will connect demand forecasting and capacity allocation with model readiness, rollout planning, launch coordination, and post-deployment learning. You will also own mode deployment beyond capacity by working with cross functional teams across research, post-training, inference and product to own mainline model deployment.

You will bring structure to constrained-capacity decisions, improve the tooling and mechanisms teams use to prioritize demand, and help new models reach users safely and efficiently. Success requires technical depth, sound judgment under ambiguity, and crisp execution across product, research, infrastructure, and operations teams.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:
  • Own cross-functional programs for Chat capacity forecasting, allocation, headroom planning, and constrained-capacity operations.
  • Build durable intake, prioritization, and decision mechanisms that connect product demand and model requirements to available serving capacity.
  • Partner with product, research, inference, fleet, and capacity teams to develop scenarios, surface tradeoffs, and drive timely allocation decisions.
  • Lead model deployment readiness and rollout planning, including serving-capacity allocation, launch sequencing, validation, and operational handoffs.
  • Establish clear readiness gates, risk reviews, rollback criteria, and escalation paths for model deployments.
  • Drive launch coordination through deployment and post-launch learning, turning recurring gaps and manual work into scalable tooling and operating practices.
  • Define and operationalize metrics for forecast accuracy, capacity utilization and headroom, deployment velocity, reliability, latency, quality, and user impact.
  • Create concise, decision-ready communications that make dependencies, risks, capacity constraints, and launch choices clear to technical and product leaders.
You might thrive in this role if you:
  • Have led complex technical programs in infrastructure, distributed systems, capacity planning, model serving, or large-scale deployment environments.
  • Can reason credibly about demand, supply, headroom, reliability, latency, and quality tradeoffs, and translate them into executable plans.
  • Have built operating mechanisms or tooling that replaced fragmented, manual workflows with scalable systems and clear ownership.
  • Are effective in high-ambiguity, constrained environments where priorities change and decisions require explicit tradeoffs.
  • Build alignment across research, engineering, product, finance or capacity planning, and operations without relying on direct authority.
  • Use metrics to guide decisions, identify bottlenecks, and demonstrate measurable improvements in throughput, predictability, or reliability.
  • Communicate with precision and can move comfortably between technical detail, operational execution, and executive-level decisions.
  • Thrive in ambiguous, scaling environments and can bring order to complex cross-functional work without losing pace.
  • Care about OpenAI's mission and about expanding responsible access to advanced AI systems.


At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

About OpenAI

OpenAI is an artificial intelligence research laboratory consisting of the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. The company was founded in 2015 by a group of technology leaders, including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, and John Schulman. OpenAI's mission is to develop and promote friendly AI for the betterment of humanity. The company has developed a number of cutting-edge AI technologies, including GPT-3, a language processing system that can generate human-like text. OpenAI has received funding from a number of high-profile investors, including LinkedIn co-founder Reid Hoffman and venture capitalist Peter Thiel.
Learn more about OpenAI
Size
100 employees
Industry
Founded
2015

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