LATAM GTM Infrastructure Lead

Google

Ciudad de México

Presencial

MXN 1.800.000 - 2.800.000

Jornada completa

Hace 3 días
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Descripción de la vacante

Google LATAM is seeking a GTM Infrastructure Practice Lead to accelerate demand for foundational cloud infrastructure across Latin America. You will partner with sales, technical specialists, and partners to scale go-to-market initiatives and surface high-value enterprise opportunities.

You will lead programmatic activations, collaborate across regional leaders, and drive growth plans with cross-functional teams to optimize execution and pipeline velocity.

Formación

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in technical pre-sales, solutions architecture, technology consulting, or commercial GTM planning for an enterprise cloud business.
  • 2 years of experience working with AI or Generative AI products in a commercial context.
  • Fluent communication in English, Portuguese, and Spanish for LATAM engagements.

Responsabilidades

  • Define and align regional GTM strategy for LATAM with global goals.
  • Drive programmatic demand generation across priority infrastructure pillars.
  • Coordinate cross-functional teams to generate early-stage enterprise pipeline.
  • Track key metrics and provide actionable insights to leadership.
  • Lead regular pipeline reviews to resolve roadblocks and scale best practices.

Conocimientos

Pre-sales experience
Solutions architecture
Technology consulting
GTM planning
Generative AI experience
Multilingual communication

Educación

Bachelor's degree or equivalent

Descripción del empleo

Google LATAM is seeking a GTM Infrastructure Practice Lead to accelerate demand for foundational cloud infrastructure across Latin America. You will partner with sales, technical specialists, and partners to scale go-to-market initiatives and surface high-value enterprise opportunities.

You will lead programmatic activations, collaborate across regional leaders, and drive growth plans with cross-functional teams to optimize execution and pipeline velocity.

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