GCP Cloud Architect
Listed on 2026-07-13
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IT/Tech
Cloud Computing: Infrastructure & Operations, AI Engineer (Applied/Software), Data Engineering
Google Cloud Platform Technical Architect
The Google Cloud Platform Technical Architect is a customer‑facing domain expert who applies broad technical skills to design and deliver modern cloud platforms, from cloud foundations and modern provisioning to migration and modernisation strategies, as well as cloud‑native, data‑driven, and AI‑enabled solutions that meet business needs by applying the most appropriate cloud deployment models and Google Cloud services for each case.
You will lead technical discussions with clients and apply your knowledge to design the best solutions for them. This role requires exceptional communication skills with both technical and non‑technical audiences, using Google Cloud services to solve our clients' business and technology challenges on a day‑to‑day basis. You will also help clients understand how cloud platforms can support AI adoption, including generative AI, machine learning, intelligent automation, AI‑assisted operations, and responsible AI practices.
- Design and deliver cloud solutions across IaaS, PaaS, and SaaS environments on Google Cloud Platform.
- Define enterprise‑scale migration strategies, including rehost, replatform, refactor, repurchase, retire, retain, and relocate.
- Architect cloud foundations, landing zones, and scalable, highly available environments, integrating on‑premises infrastructure with Google Cloud.
- Lead technical workshops, assessments, and migration implementations, continuously seeking opportunities to automate processes and remediate technical debt.
- Drive the design of AI‑ready cloud and data platforms that support ingestion, storage, governance, analytics, model deployment, monitoring, and integration with enterprise applications.
- Collaborate with teams across sectors such as financial services, public sector, insurance, telco, and media to solve complex business challenges using cloud, automation, and AI‑enabled solutions.
- Consult on AI governance, responsible AI, data privacy, security, model risk, and compliance for AI‑enabled workloads.
Skills & Qualifications
- Extensive experience designing and architecting solutions on Google Cloud Platform across core services: compute, containers, storage, databases, networking, security, observability, Dev Ops, and cost management.
- Broad hands‑on knowledge of Google Cloud services such as Google Kubernetes Engine, Terraform, Anthos, Apigee, Cloud Composer, Dataflow, Pub/Sub, Looker, Vertex AI, Model Garden, Document AI, Gemini, and other data, analytics, and AI services.
- Experience designing and deploying secure, scalable, and highly available cloud environments, including resource hierarchy, IAM, shared VPC, hub‑and‑spoke networking, guardrails, logging, monitoring, governance, and security controls.
- Strong experience with containerised solutions, Kubernetes production platforms, microservices, and Kubernetes management on Google Cloud.
- Hands‑on experience with Infrastructure as Code and automation tools, particularly Terraform and CI/CD platforms such as Jenkins, Git Hub Actions, Git Lab CI/CD, Cloud Build, or Cloud Deploy.
- Demonstrated knowledge of generative AI solution patterns, generative AI services, and AI‑ready architecture, with awareness of responsible AI, data privacy, security, and auditability.
- Strong analytical and technical skills, with the ability to learn new tools, services, and methodologies as the market evolves.
- Excellent English verbal and written communication skills, and the ability to engage effectively with both technical and non‑technical stakeholders.
- Ability to work well under pressure, respond quickly to client needs, and adapt to changing requirements.
- Google Cloud certifications such as Professional Cloud Architect, Professional Cloud Dev Ops Engineer, Professional Cloud Security Engineer, Professional Cloud Network Engineer, Professional Data Engineer, Professional Machine Learning Engineer, or Associate Cloud Engineer are highly desirable.
- Good to have:
Pre‑sales or commercial experience, on‑premises infrastructure management experience, and experience with MLOps, AIOps, and cloud security, compliance, and governance frameworks for…
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