Revenue Operations Lead

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 built your career at the intersection of strategy, analytics, and operations, with experience across GTM Strategy & Operations, Business Operations, Strategic Finance, Revenue Strategy, Revenue Operations, or similarly analytical roles in high-growth technology businesses. You may have started your career in consulting, banking, finance, engineering, or another analytically rigorous environment before moving into operating roles.
• 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.
• Have personally owned complex commercial analyses and strategic decisions - such as pricing and packaging, segmentation, capacity and coverage models, unit economics, investment decisions, or GTM design - and can translate rigorous analysis into a clear recommendation and operating plan.
• Are exceptionally analytical and comfortable doing the work yourself. You can structure ambiguous business questions, interrogate messy data, build rigorous analyses and models, and use them to drive decisions with senior leadership.
• Bring strong judgment across GTM strategy, operating models, target setting, capacity planning, forecasting, pipeline management, and executive reporting.
• Can both architect and critically evaluate commercial systems. You have made consequential decisions around CRM and GTM architecture, including evaluating tools, designing data models and workflows, leading implementations or migrations, and establishing the governance required to make those systems reliable.
• Have a track record of increasing scope and responsibility, including stepping into ambiguous or underbuilt environments and leaving behind stronger systems, processes, and organizations.
• 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 strategy and execution: you are equally comfortable defining the long-term commercial operating model, analyzing a strategic business question, and fixing the workflow, forecast, dashboard, 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.