GCP Cloud Architect

Role Description

Job Description - GCP Cloud Architect with Data & AI Experience

Function: Digital Engineering

Role Level: Cloud Architect - GCP (L4)

Location: Offshore

Role Overview

The GCP Cloud Architect (L4) defines and leads enterprise-scale cloud solution architecture on Google Cloud Platform (GCP). The role requires broad expertise across GCP infrastructure, security, networking, integration, operations, and platform services, with practical architectural knowledge of GCP data and AI services. The architect guides service selection, integration, security, scalability, reliability, governance, and cost optimization. This is not a Data Architect, Data Engineer, ML Engineer, or Data Scientist role.

Key Responsibilities

• Define end-to-end GCP solution architecture across infrastructure, networking, security, identity, integration, operations, data, and AI service considerations.
• Translate business and technical requirements into scalable, secure, resilient, and cost-effective GCP architectures.
• Recommend GCP services and patterns based on workload needs, non-functional requirements, enterprise standards, and delivery constraints.
• Design solutions using GCP data services such as BigQuery, Cloud Storage, Pub/Sub, Dataflow, and Cloud Composer, without owning detailed data engineering design.
• Design solutions using Vertex AI and related AI services, focusing on integration, security, deployment, operations, governance, and responsible AI.
• Define networking, IAM, encryption, secrets, data protection, logging, monitoring, and security controls.
• Establish patterns for APIs, event-driven integration, managed compute, serverless services, and enterprise connectivity.
• Design Infrastructure as Code, CI/CD, environment strategy, configuration management, and DevSecOps practices.
• Define availability, disaster recovery, observability, supportability, performance, capacity, and reliability requirements.
• Collaborate with application, platform, data, AI/ML, security, infrastructure, and operations specialists for cohesive delivery.
• Conduct architecture reviews, manage technical risks and dependencies, and ensure alignment with enterprise standards.
• Provide technical leadership, architecture governance, stakeholder communication, and mentoring.
  
  

Required Skills And Experience

• 8-10 years of experience in cloud architecture, solution architecture, platform engineering, infrastructure, or related technology roles.
• Strong expertise in GCP architecture across compute, storage, networking, IAM, security, integration, monitoring, and operations.
• Experience designing secure, scalable, resilient, and highly available enterprise solutions on GCP.
• Working architectural knowledge of BigQuery, Cloud Storage, Pub/Sub, Dataflow, and Cloud Composer, including service selection, integration, security, scalability, and operations.
• Working architectural knowledge of Vertex AI and related AI services, including capabilities, integration, security, governance, deployment, and operations.
• Ability to collaborate with Data Architects, Data Engineers, ML Engineers, and Data Scientists without owning their specialist design or engineering responsibilities.
• Strong understanding of cloud networking, IAM, encryption, secrets, policies, security controls, and zero-trust principles.
• Experience with Infrastructure as Code, preferably Terraform, and CI/CD or DevSecOps practices.
• Experience with monitoring, reliability, disaster recovery, cost optimization, and cloud operations.
• Strong leadership, communication, stakeholder management, problem-solving, and governance skills.
  
  

Preferred Qualifications

• Google Cloud Professional Cloud Architect certification.
• Exposure to enterprise analytics, data platforms, machine learning, or Generative AI solutions on GCP.
• Familiarity with Vertex AI, Generative AI services, RAG patterns, and responsible AI principles.
• Familiarity with APIs, event-driven architecture, Cloud Run, integration patterns, and applications consuming data or AI services.
• Kubernetes or GKE experience is nice to have.