Google Cloud & AI Solutions Engineer

Overview

The role of Cloud & AI Solutions Engineer involves supporting both pre-sales and post-sales technical activities across the Google Cloud platform. This position encompasses leading technical discovery efforts, architecting enterprise-grade Google Cloud environments, deploying scalable cloud workloads, and designing AI and generative AI solutions to accelerate client digital transformation.

Key Responsibilities

• Partner with sales teams to guide technical discovery, evaluate customer needs, respond to RFPs/RFIs, and develop Statements of Work (SOWs).
• Create enterprise architecture designs, cost forecasts, and migration roadmaps leveraging Google Cloud Platform (GCP).
• Deliver compelling technical demos and presentations aimed at technical teams and executive stakeholders.
• Architect, deploy, and automate Google Cloud Landing Zones including organization hierarchy setups, identity and access management (IAM), virtual private cloud (VPC) networking, security boundaries, and billing structures.
• Develop and maintain Infrastructure as Code (IaC) processes primarily with Terraform.
• Lead full-cycle cloud workload migration and the deployment of modern applications using Compute Engine, Google Kubernetes Engine (GKE), Cloud Run, Cloud SQL, and Spanner.
• Design, build, and deploy production-grade AI Agents utilizing Vertex AI, Gemini models, and agent orchestration frameworks such as LangChain, LlamaIndex, or the Google GenAI SDK.
• Implement Retrieval-Augmented Generation (RAG) pipelines, enhance search grounding, and integrate enterprise tool use and function calling.
• Create practical Proof of Concepts (PoCs) that showcase agentic workflows, document automation, and generative AI applications during both sales and delivery phases.

Educational Background

Applicants should hold a Bachelor’s degree in Computer Engineering, Computer Science, Artificial Intelligence, or a related technical field.

Experience Requirements

• Between 4 to 6 years of relevant technical experience covering cloud architecture, DevOps, and solution delivery, integrating both pre-sales and post-sales roles.
• At least 1 to 2 years of practical experience in developing applied generative AI solutions, RAG pipelines, or agentic AI workflows.

Desired Qualifications and Skills

• Proficiency in solution architecture combined with consultative selling techniques.
• Strong hands-on technical skills and problem-solving capabilities.
• Demonstrated experience managing end-to-end project delivery with ownership.
• Ability to communicate complex cloud and AI concepts in business terms effectively.
• Essential certification: Google Cloud Certified Professional Cloud Architect or Professional Data Engineer.
• Preferred additional certifications: Google Cloud Professional Machine Learning Engineer or Google Cloud Gen AI Leader/Developer.