Responsibilities

• Architect and Scale an AI-Native Marketing-to-Revenue Engine
• Redesign the marketing operating model to connect targeting, activation, journey orchestration, analytics, and pipeline performance into a predictable, scalable marketing-to-revenue system.
• Build AI-enabled workflows that move faster and with higher signal, including segmentation, scoring, routing, and lifecycle progression across the customer journey.
• Translate growth strategy into measurable operating plans tied directly to pipeline contribution, conversion, and revenue outcomes.
• Turn Signal, Intent, and Performance Data into Action
• Establish AI-assisted funnel intelligence to detect conversion gaps, pipeline leakage, and journey friction early, then drive interventions that improve flow from engagement to pipeline.
• Build decision-ready dashboards and performance narratives that connect marketing activity to revenue impact, with clear recommendations and owners.
• Use experimentation and advanced analytics to improve targeting precision, sales velocity, and demand efficiency.
• ICP, segmentation, and account prioritization
• Operationalize ICP and segmentation using enrichment, intent, and performance data; keep targeting logic current as results change.