Vp, Ai-native Ops & Automation, Gtm

Algolia Algolia · Enterprise · United States · Remote · CEO Office

This role is responsible for transforming Algolia's go-to-market (GTM) organization by architecting and scaling systems, workflows, decision models, and automation capabilities that embed AI and automation into the full customer lifecycle. The goal is to create an intelligent execution engine that improves growth quality, forecasting precision, productivity, and operating leverage, moving beyond traditional RevOps by redesigning the revenue operating system.

What you'd actually do

  1. Assess and redesign core GTM workflows across pipeline generation, forecasting, renewals, customer expansion, and operational planning
  2. Apply AI, analytics, and automation capabilities across structured and unstructured GTM data sources
  3. Build and execute a multi-quarter transformation roadmap aligned to measurable business outcomes
  4. Define KPI frameworks tied to forecast accuracy, pipeline conversion, productivity, customer outcomes, and operational efficiency

Skills

Required

  • Systems thinking
  • Redesigning organizations for scale, velocity, and clarity
  • Communication and influence skills across technical and non-technical stakeholders
  • 15+ years of experience in Revenue Operations, Business Operations, Enterprise Transformation, Consulting, or adjacent leadership roles
  • Strong working knowledge of AI/ML applications, automation tooling, data architectures, and modern GTM systems ecosystems
  • Demonstrated success leading large-scale operational transformation initiatives with measurable business impact

Nice to have

  • Experience within high-growth SaaS, enterprise software, or AI-native organizations
  • Familiarity with enterprise AI tooling ecosystems, forecasting systems, NLP applications, and autonomous workflow tooling
  • Experience building operational governance and performance measurement frameworks at scale
  • Exposure to enterprise customer motions and complex global GTM organizations

What the JD emphasized

  • AI-native execution
  • AI, automation, process intelligence, and real-time decision systems
  • embedding AI and automation capabilities across structured and unstructured GTM data sources
  • deploy production-grade AI and automation solutions embedded into daily workflows
  • AI-native workflows and operating practices
  • AI-driven systems
  • responsible AI usage
  • Strong working knowledge of AI/ML applications, automation tooling, data architectures, and modern GTM systems ecosystems
  • Demonstrated success leading large-scale operational transformation initiatives with measurable business impact