Head of Revenue Systems & Technology

Responsibilities

• Architect and ship Exa's end-to-end revenue tech stack: CRM (Salesforce), sales engagement, customer success, CPQ/billing, forecasting, conversational intelligence — unified by one extensible data layer.
• Integrate the marketing ops (MOPS) stack into the revenue layer for pipeline tracking and intent scoring.
• Own the CRM end-to-end: object model, automation, approval workflows, pipeline configuration, forecasting methodology, data hygiene.
• Deploy AI agents across the customer journey: lead routing, deal scoring, next-best-action, real-time pipeline risk detection, renewal and expansion signals.
• Build the infrastructure that lets those agents run reliably at scale: structured data pipelines, event-driven triggers, API orchestration, feedback loops.
• Own build-vs-buy decisions; default to open, composable platforms; add a middleware layer so new tools plug in cleanly.
• Keep a canonical data model across every GTM system so analytics, reporting, and agents all run off one source of truth.
• Stand up forecasting and pipeline analytics: stage velocity, conversion, segment health, and the leading indicators that feed weekly business reviews and board reporting.
• Build the dashboards that give Revenue Leadership real-time visibility into pipeline, forecast trajectory, and customer health.
• Collaborate in building out the Revenue Systems team over time.

Requirements

• 10+ years architecting revenue systems end-to-end (sales ops, rev ops, or GTM systems) at high-growth B2B companies, with 5+ years owning the stack yourself.
• Deep Salesforce experience: built instances from scratch and scaled them through hypergrowth.
• Hands-on integration experience with the full GTM stack: CRM, MOPS (Marketo/HubSpot), SEP (Outreach/Salesloft), CSP (Gainsight), CPQ, forecasting (Clari/BoostUp), conversational intelligence (Gong/Chorus).
• Experience building for extensibility, data integrity, and composability; strong opinions on canonical data models and build-vs-buy decisions.
• Experience designing and deploying AI-powered, agentic workflows inside GTM systems — architecting custom agent-driven processes.
• Comfortable operating as both architect and builder in a high-velocity startup where priorities shift regularly.

Nice-to-Haves

• Experience building GTM systems for companies selling developer tools, APIs, or data infrastructure to engineering-led buyers.
• Experience supporting both product-led growth (self-serve API adoption, usage-based pricing) and enterprise sales within a single architecture.
• Knowledge of consumption- or usage-based billing and the complexity it introduces across CRM, CPQ, and revenue recognition.
• Experience building and scaling revenue systems infrastructure through an IPO or major liquidity event.