Operating Executive · Revenue Infrastructure
I build revenue infrastructure for complex B2B tech — multi-product, multi-segment, mid-integration. AI governance, M&A, forecasting, and the programs that hold it together. 20 years across RevOps and GTM.
Background
My career has been a repeating pattern: take a fragmented, reactive revenue function and rebuild it as a proactive operating system. The tools and scale have changed — the discipline hasn't.
Revenue modeling, G&A forecasting, and global sales analytics at scale. Built the financial rigor that everything else runs on — including CFO-level forecast models used for quarterly investor guidance.
Finance logic met go-to-market execution. Built forecasting infrastructure, a competitive intelligence program, and the sales performance systems that drove 50% YoY new sales growth over six consecutive quarters.
Four years, four consecutive years of 50%+ ARR growth. Built a 43-person global RevOps org from scratch across NA, EMEA, and APAC — forecasting, CPQ, pricing, sales specialization, and international expansion.
Inherited nothing. Built forecasting to <3% variance, a custom CPQ for site-level selling, a bundle pricing framework that drove 13% ARPU lift, and the full GTM tech stack — from a standing start.
Applied the playbook across multiple companies simultaneously — GTM builds, funnel diagnostics, pricing strategy, interim CRO, and CRM rebuilds for a range of B2B tech companies.
Everything above, running in parallel. Eight M&A integrations without pipeline disruption, AI governance built from zero, PS and CS infrastructure stood up for the first time, and a multi-LOB operating model across a high-inorganic-growth platform.
Selected Work
Scope generalized where current engagements require it. Detail available on request.
Full GTM organization. AI was being adopted inconsistently — no ownership, no governance, duplicated vendors, real risk of bad outputs reaching customers.
Sprawl, not strategy. Tools accumulated without accountability structures, solution design standards, or any mechanism to measure whether adoption generated return.
Audited all AI tool usage across the GTM org. Named agent ownership per tool and use case. Built a solution design process (problem → pilot → scale). Replaced legacy tools with AI-native alternatives inside existing seller workflows.
30% reduction in GTM tech spend with expanded functional capability. Pre-call intelligence delivered directly to seller inboxes. Governance model with clear decision rights in place across the org.
Full commercial sales org. Bootcamp certification and post-bootcamp ramp — from initial hire through quota attainment readiness.
A 100% bootcamp pass rate was masking real rep readiness gaps. Post-bootcamp onboarding ran on manual weekly check-ins that couldn't scale. Problems surfaced at quota, not certification.
Restructured bootcamp certification around actual readiness indicators. Layered an AI system on top: machine-generated, rubric-driven onboarding plans built from the company's own winning conversations, segmented by vertical.
Real readiness problems surfaced and addressed before reps hit quota. Manual check-in overhead eliminated. Each rep's onboarding path tied to the actual conversations that close deals in their vertical.
Six acquisitions across two companies — each with distinct sales motions, comp structures, CRM configurations, and GTM approaches requiring rapid integration without disrupting pipeline.
Each acquisition risked rep attrition, pipeline loss, and delayed revenue recognition. Running five simultaneously amplified every coordination failure and left no margin for slow starts.
A repeatable GTM integration playbook covering CRM configuration, comp harmonization, territory and account mapping, product positioning alignment, and a unified reporting layer — applied and refined across six successive integrations.
Six full GTM integrations completed without material pipeline disruption. Each successive acquisition absorbed faster than the last as the playbook compounded. $6M+ in incremental partner ARR built from zero in parallel.
Writing
Two threads: operating revenue infrastructure at scale, and closing the gap between AI power users and everyone else.
Writing in progress
Writing in progress
Advisory
Selective advisory work for PE-backed and growth-stage SaaS companies on revenue operations, AI governance, pricing, and partner strategy.
Open to operating executive roles in Revenue Operations or broader cross-functional leadership, and select advisory engagements.
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