Summary
✨ AI‑Generated
A Cloud & AI Solutions Engineer will lead technical discovery, design enterprise cloud architectures, deliver production-grade workloads, and develop custom generative AI agents and solutions. The role spans pre-sales architecture and post-sales implementation, including migration planning, automation, technical demonstrations, executive presentations, and customer modernization initiatives.
Highlights
Hybrid pre-sales and post-sales role combining enterprise cloud architecture, hands-on delivery, and cutting-edge generative AI work. Offers exposure to technical discovery, executive presentations, large-scale cloud migration, and custom AI solution development.
Description
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 SellingHands-on Technical Agility & TroubleshootingEnd-to-End Delivery AccountabilityTranslating Complex AI/Cloud Concepts to Business ValueRequired: 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.
