Google Cloud AI Architect

AVENSYS CONSULTING PTE. LTD.; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

A leading cloud solutions provider in Singapore is seeking a Google Cloud AI Architect to design and lead scalable AI solutions on Google Cloud Platform. The ideal candidate will have over 7 years of experience in software or cloud engineering, with strong hands-on experience in GCP and AI/ML workloads. This role involves overseeing GCP architecture, guiding full-stack engineers, and ensuring compliance with security and regulatory requirements. Excellent communication skills and ability to collaborate with diverse stakeholders are essential. Competitive compensation and opportunities for professional growth are offered.

Qualifications

• 7+ years of software or cloud engineering experience.
• 3–4 years hands-on with GCP.
• Strong experience with microservices and APIs on GCP.

Responsibilities

• Design end-to-end AI solutions on GCP.
• Review designs and provide mentorship to engineering teams.
• Establish DevOps/MLOps practices: CI/CD and model deployment.

Skills

GCP architecture

AI/ML workloads

Cloud-native architectures

Infrastructure as code

Communication skills

Education

Bachelor’s degree in Computer Science or Engineering

Tools

Terraform

BigQuery

Pub/Sub

Job description

Job Overview

The Google Cloud AI Architect is responsible for designing and leading end‑to‑end solutions on Google Cloud Platform (GCP), from cloud foundation and security to data and AI services (for example, Gemini / Vertex AI), ensuring they are scalable, secure, and cost‑efficient. This role provides technical leadership to full‑stack engineers and partners with product and business stakeholders to deliver production‑grade AI solutions.

Key Responsibilities

• Own overall GCP architecture including projects, networking, IAM, security, monitoring, and cost management.
• Design end‑to‑end AI solutions using Google services (for example, Vertex AI / Gemini, BigQuery, Document AI, Pub/Sub, Cloud Storage).
• Translate business and product requirements into technical roadmaps, reference architectures, and solution designs.
• Define standards and best practices for cloud, data, and AI workloads, including reliability, observability, and performance.
• Guide full‑stack engineers on implementation, integration patterns, and non‑functional requirements.
• Establish DevOps / MLOps practices: CI/CD, infrastructure as code, model deployment strategies, and environment management.
• Ensure compliance with security, privacy, and regulatory requirements, including data residency and access control.
• Review designs and code, perform architecture reviews, and provide mentorship to engineering team members.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 7+ years of experience in software or cloud engineering, including at least 3–4 years hands‑on with GCP.
• Strong experience designing cloud‑native architectures (microservices, APIs, event‑driven systems) on GCP.
• Hands‑on experience with AI/ML workloads on Google Cloud (for example, Gemini / Vertex AI, custom models, vector search, or document/vision/language APIs).
• Solid understanding of GCP networking, IAM, security, VPC design, and enterprise integration patterns.
• Experience with infrastructure as code (Terraform, Deployment Manager, etc.) and CI/CD pipelines.
• Excellent communication skills and ability to work with both technical and non‑technical stakeholders.

Preferred Qualifications

• Google Cloud Professional Cloud Architect and/or Professional Machine Learning Engineer certifications.
• Experience leading multi‑project or multi‑tenant GCP environments in production.
• Experience setting up or governing data platforms on GCP (BigQuery, Dataflow, Dataproc, Pub/Sub).