Cloud & AI Solutions Architect — GCP, Vertex AI & AI Agents

Advanced Business Computing; Doha; On-site; QAR 300,000 - 460,000; Full time

Job summary

Advanced Business Computing is seeking a Cloud & AI Solutions Engineer to drive pre-sales solution engineering and hands-on post-sales delivery across Google Cloud technologies. You will architect landing zones, deploy workloads, and build AI agents using Vertex AI and LangChain to modernize customer environments.

Ideal candidates have 4–6 years in cloud architecture and 1–2+ years delivering generative AI solutions, with a Google Cloud certification (Architect or Data Engineer) preferred.

Qualifications

• Bachelor’s degree in Computer Engineering, Computer Science, Artificial intelligence or related field.
• 4–6 years in cloud architecture, DevOps, and delivery across pre- and post-sales.
• 1–2+ years building applied generative AI solutions, RAG pipelines, or agentic workflows.
• Google Cloud Certified Professional Cloud Architect or Professional Data Engineer required.

Responsibilities

• Co-lead technical discovery with sales, draft SOWs and respond to RFPs.
• Design target-state enterprise architectures and migration blueprints on GCP.
• Deliver technical demonstrations and executive presentations to leaders.

Skills

Solution Architecture

Consultative Selling

Delivery Accountability

Business Value Translation

Cloud Computing

Education

Bachelor’s degree in Computer Engineering / CS / AI

Tools

Terraform

Google Cloud Platform

Google Kubernetes Engine

Vertex AI

GenAI tools

Job description

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

• 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.