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 (Ia C) 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., Lang Chain, Llama Index, or Google Gen AI SDK). Build Retrieval‑Augmented Generation (RAG) pipelines, grounding search, and enterprise tool‑use/function‑calling integrations. Develop functional Proof of Concepts (Po Cs) 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, Dev Ops, 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. #J-18808-Ljbffr