Google Cloud & AI Solutions Engineer

Job Scope The Cloud & AI Solutions Engineer is responsible for driving both pre-sales solution engineering and hands-on post-sales delivery across the full spectrum of Google Cloud technologies. This includes leading technical discovery, architecting enterprise Google Cloud landing zones, deploying production-grade cloud workloads, and designing and developing custom AI agents and generative AI solutions to drive customer modernization. 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. Education 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. 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.