Google Cloud Pre Sales Consultant Lead

• Do you thrive on designing intelligent, scalable solutions that combine cloud infrastructure with cutting‑edge AI?
• Are you excited by the opportunity to help customers adopt Google Cloud Platform and modernize their businesses through Generative AI?
• Do you enjoy partnering with sales, delivery teams, and customers to architect solutions that deliver measurable impact?

Practical Information

Location: Paris or Montpellier, France | Reports to: PreSales Team Lead | Work Arrangement: Hybrid | Visa Requirements: Valid visa for France | Language Requirements: Fluent in English and France

As our new  Cloud Solution Architect & AI Specialist , you will help customers adopt  Google Cloud Platform (GCP) and design scalable solutions that integrate  AI, cloud infrastructure, and data services . You will translate business needs into architectures using technologies like  Gemini Enterprise ,  GKE , and  Vertex AI , supporting customer innovation and cloud modernization. Working within our  Google Cloud & AI practice , you will collaborate across Sales, Delivery, Engineering, and customer teams to design value‑driven, production‑ready solutions that accelerate transformation. 

Key Responsibilities

• Lead workshops, discovery assessments, and readiness evaluations to understand customer requirements across cloud, data, and AI adoption 
• Translate customer pain points into high‑value use cases integrating enterprise data with Generative AI and GCP-native services 
• Design end‑to‑end architectures for  AI (Gemini Enterprise, Vertex AI) ,  Cloud Infrastructure (GKE, hybrid/multi‑cloud networking) , and  Data Services (BigQuery, Cloud Storage, Dataflow) including RAG patterns 
• Produce solution blueprints, architecture diagrams (HLD/LLD), technical PoCs, and demos in collaboration with engineering teams 
• Build proposals, SOWs, estimates, and respond to RFI/RFPs with security, scalability, and TCO considerations 
• Support the sales cycle by addressing technical objections related to data privacy, AI governance, infrastructure design, and implementation feasibility