Job details
- 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: Services Director | Work Arrangement: Hybrid | Visa Requirements: Valid visa for France | Language Requirements: Fluent in English and France
The Role
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
