Google Cloud and AI Solutions Engineer

Main Duties and Responsibilities Pre-Sales & Solution Architecture: Co-lead technical discovery with the sales team, qualify client requirements, author RFP/RFI responses, and draft statements of work (SOWs). Design target-state enterprise architectures, cost estimations, and architectural migration blueprints on GCP. Deliver high-impact technical demonstrations and executive presentations to technical leads and C-level stakeholders. Cloud Infrastructure Delivery & Migration (Post-Sales): Architect, deploy, and automate enterprise-grade Google Cloud Landing Zones (organization hierarchy, IAM, VPC networking, security perimeters, and billing models). Build and manage Infrastructure as Code (IaC) pipelines using Terraform . Lead end-to-end workload migration and modern application deployment (compute engines, Google Kubernetes Engine / GKE, Cloud Run, Cloud SQL, Spanner). Applied AI & Agentic Development: Design, build, and deploy production-ready AI Agents leveraging Vertex AI , Gemini models, and agentic orchestration frameworks (e.g., LangChain, LlamaIndex, or Google GenAI SDK). Build Retrieval-Augmented Generation (RAG) pipelines, grounding search, and enterprise tool-use/function-calling integrations. Develop functional Proof of Concepts (PoCs) demonstrating agentic workflows, document processing, and generative AI use cases during pre-sales and post-sales delivery. Position Requirements Solution Architecture & Consultative Selling Hands-on Technical Agility & Troubleshooting End-to-End Delivery Accountability Translating Complex AI/Cloud Concepts to Business Value Required: Google Cloud Certified Professional Cloud Architect or Professional Data Engineer. Preferred: Google Cloud Professional Machine Learning Engineer or Google Cloud Gen AI Leader / Developer credentials.

Desired Candidate Profile

Bachelor s degree in Computer Engineering, Computer Science, Artificial intelligence or any other related field Experience 4 to 6 years of technical engineering experience spanning cloud architecture, DevOps, and delivery (combining pre-sales and post-sales). 1 to 2+ years of hands-on experience building applied generative AI solutions, RAG pipelines, or agentic workflows.