Revenue Operations

Prime Intellect•San Francisco, CA

14d•Remote

About The Position

Building Open Superintelligence Infrastructure Prime Intellect is building the open superintelligence stack - from frontier agentic models to the infra that enables anyone to create, train, and deploy them. We aggregate and orchestrate global compute into a single control plane and pair it with the full RL post-training stack: environments, secure sandboxes, verifiable evals, and our async RL trainer. We enable researchers, startups and enterprises to run end-to-end reinforcement learning at frontier scale, adapting models to real tools, workflows, and deployment contexts. We recently raised $15mm in funding (total of $20mm raised) led by Founders Fund, with participation from Menlo Ventures and prominent angels including Andrej Karpathy (Eureka AI, Tesla, OpenAI), Tri Dao (Together AI), Dylan Patel (SemiAnalysis), Clem Delangue (Huggingface), Emad Mostaque (Stability AI) and many others. Your Role Own the end-to-end revenue operations engine across Sales, Growth, and Customer teams. You will design the systems, data models, and processes that make revenue predictable and GTM execution surgical. Own CRM architecture, forecasting, compensation design, deal desk, and analytics. Turn noisy signals across compute usage, post-training work, and pipeline into clear decisions and repeatable motion. This is a foundational role for someone who wants to be the backbone of how Prime Intellect goes from deals to durable revenue.

Requirements

5+ years in Revenue Operations, Sales Operations, or Growth Operations at B2B SaaS or infrastructure companies.
Deep hands-on CRM experience (HubSpot, Salesforce, or similar) where you owned data model, workflows, and reporting.
Strong analytical skill set - SQL or BI tools, cohort analysis, funnel modeling, forecasting.
Experience partnering closely with Sales leadership on pipeline reviews, forecasting, and compensation design.
Proven track record building processes that scale from early-stage chaos to repeatable motion.
Comfortable going from strategy (what should we measure) to execution (how do we implement it in tools).
Detail oriented with a bias for clean data and operational rigor.
Thrive in fast-moving, high-ambiguity environments where the answer is often "we have to design it."

Nice To Haves

Experience with usage-based or consumption-based pricing and billing.
Familiarity with compute marketplaces, cloud billing, or infrastructure cost modeling.
Background working with product analytics and connecting product signals to GTM actions.
Early-stage experience where you were the first RevOps hire standing up the function.

Responsibilities

Own GTM systems across the funnel - CRM, marketing automation, product analytics, billing, and data warehouse.
Design and maintain CRM architecture so that pipeline, stages, and fields reflect reality and support accurate forecasting.
Build and standardize reporting for leadership: pipeline health, conversion rates, cohort performance, NRR, GRR, compute GMV.
Partner with Head of Enterprise Sales and AEs on territory design, quota setting, compensation plans, and performance tracking.
Run deal desk for complex deals - pricing structure, approvals, non-standard terms.
Connect product usage and compute consumption data to revenue metrics for usage-based and hybrid models.
Define and implement lead routing, SLAs, and handoffs between Marketing, Sales, TAM, and Solutions.
Automate repetitive GTM workflows so Sales and CS can focus on customers, not admin.
Create and maintain a single source of truth for revenue data across tools and teams.
Partner with Finance on revenue recognition, forecasting assumptions, and board reporting inputs.
Evaluate and manage the GTM tech stack - select tools, own vendor relationships, ensure adoption.
Build documentation and playbooks for how we run revenue operations as the team scales.