Summary
Midis Group is hiring a Google Cloud and AI Solutions Engineer in Qatar. The role covers pre-sales discovery and solution architecture, as well as hands-on delivery of Google Cloud landing zones, workload migrations, and cloud deployments. The engineer will also develop generative AI agents, RAG pipelines, and proofs of concept using tools such as Vertex AI and Gemini. Applicants need a related bachelor’s degree, 4 to 6 years of technical engineering experience, 1 to 2+ years building applied generative AI solutions, and a Google Cloud Professional Cloud Architect or Professional Data Engineer certification.
The posting
As published on midisgroup.com. Pulled from the employer's site and shown as they wrote it.
Job Title
Google Cloud and AI 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.
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.
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.