Revenue Operations Lead

About the Company

The OpenAI Deployment Company ("DeployCo") is the deployment arm of OpenAI, purpose-built to deliver enterprise AI transformation at scale. As model capabilities accelerate, deployment has become the primary constraint to realizing AI value creation within large enterprises. DeployCo bridges that gap.

Our ambition is to build the company that defines AI deployment. We operate at the intersection of cutting-edge AI, enterprise transformation, and scaled services delivery. We partner with enterprise customers to identify where AI can transform their businesses and build solutions leveraging OpenAI's models and products. We work with many of the world's largest and most influential companies to solve their most complex business challenges using the latest advances in AI.

People who thrive at DeployCo get excited about ambitious and complex work. We are deep believers in the future with AI. We execute quickly, value intellectual honesty, and obsess over the solutions we build for our customers.

DeployCo is being built from the ground up as a subsidiary of OpenAI and funded with a partnership of outside investors.

About the Role

We are seeking a Revenue Operations Lead to build the commercial operating system for DeployCo from inception through scale. This is a foundational role responsible for turning a high-ambiguity enterprise deployment motion into a repeatable, data-driven, AI-native revenue engine.

This role is not a conventional RevOps support function. You will be expected to operate as a strategic partner to DeployCo leadership, an architect of systems and process, and a hands-on builder who can turn ambiguous commercial questions into clear operating mechanisms. You will own the rhythms, metrics, workflows, and source-of-truth systems that allow DeployCo to scale across OpenAI-sourced opportunities, DeployCo-originated enterprise demand, partner-led deployments, renewals, expansions, and new commercial motions.

Initially, this role will operate as a player-coach. You will build the first versions of the pipeline and forecast process, account staffing model, qualification standards, executive business reviews, deal governance, customer lifecycle reporting, and revenue planning infrastructure. Over time, you will grow a Revenue Operations organization that can support a large, global, high-performance AI deployment business without losing speed or precision.

Your day-to-day will include designing operating rhythms, pressure-testing pipeline quality, building executive-ready reporting, running cross-functional planning processes, partnering with Finance on targets and capacity, working with Legal and Finance on deal desk and quote-to-cash workflows, identifying gaps in field execution, and building AI-native systems that reduce manual coordination and improve decision quality.

You will partner closely with DeployCo's CEO, GTM leadership, OpenAI GTM, Finance, Legal, Product, Delivery, Data, and Systems teams.

In this role, you will:

• Build and own DeployCo's Revenue Operations function, including GTM planning, forecasting, pipeline governance, capacity planning, compensation operations, revenue analytics, deal operations, and commercial systems.
• Design, build, and manage the core operating rhythms for the business, including forecasting, pipeline council, deal reviews, MBRs/QBRs, board/investor reporting inputs, and executive operating reviews.
• Own the source of truth for the commercial funnel, from opportunity intake through qualification, scoping, proposal, contracting, deployment, and expansion.
• Partner with Finance and GTM leadership to translate company goals into segment-level targets, coverage models, hiring plans, productivity assumptions, and investment priorities.
• Stand up the CRM and adjacent GTM systems architecture, ensuring clean data, strong process governance, scalable workflows, and reliable reporting for leaders and operators.
• Translate recurring customer, field, and delivery patterns into structured inputs for product, enablement, partner strategy, and operating-model decisions.
• Identify the highest-leverage operational constraints in the business and drive them to resolution across Sales, OpenAI GTM, Delivery, Product, Finance, Legal, Data, and Systems.
• Build executive-grade dashboards and operating readouts that make performance, risks, tradeoffs, and priorities clear to DeployCo leadership, OpenAI leadership, and investors.

You may thrive in this role if you:

• Have 10-15+ years of experience across Revenue Operations, GTM Strategy and Operations, Business Operations, Strategic Finance, Sales Operations, or related roles in high-growth technology, AI, enterprise software, infrastructure, or services businesses.
• Have built or materially scaled a commercial operating system in a high-ambiguity environment, ideally where the company was still defining its segments, motions, metrics, systems, and operating cadences.
• Bring strong judgment across GTM strategy, operating models, target setting, capacity planning, forecasting, pipeline management, and executive reporting.
• Are deeply analytical and can translate messy commercial and operational data into clear recommendations, operating plans, and leadership decisions.
• Have strong systems instincts, including experience with Salesforce or equivalent CRM platforms, BI/reporting tools, workflow automation, data governance, and AI-enabled internal tooling.
• Understand complex enterprise sales and delivery motions, including multi-stakeholder buying committees, services-heavy deployments, partner involvement, custom scopes, non-standard deal structures, and long implementation cycles.
• Can move fluidly between ideas and execution: you are comfortable defining the long-term operating model and also fixing the dashboard, workflow, forecast, or data issue blocking a decision today.
• Have executive presence and can influence senior stakeholders across technical and non-technical teams with clarity, rigor, and a best-for-the-business mindset.
• Thrive in fast-moving, ambiguous environments with frequent context switching, expansive ownership, and a high bar for output quality.
• Are energized by the opportunity to define how AI-native revenue operations should work inside the company built to define enterprise AI deployment.