Google AI Architect

Experteer Overview In this role you will architect and deliver enterprise AI platforms on Google Cloud, leveraging Vertex AI and Gemini to scale production solutions. You’ll align AI initiatives with the wider tech strategy, shaping data pipelines, model lifecycles, and CI/CD pipelines. You’ll lead secure, governance-aware deployments and drive GenAI-enabled software across diverse client environments. This is a high-impact opportunity to advance AI-driven transformation at scale within a leading consulting firm. Compensation / Benefits * Architect and design enterprise-grade AI applications and platforms for production-scale deployment * Integrate and fine-tune LLMs and AI/ML models into enterprise apps with production-grade deployment, inference, and monitoring * Collaborate with enterprise architects to ensure AI solutions align with governance and standards * Develop cloud-native solutions on hyperscalers (GCP/AWS/Azure) using containers, serverless, and managed DBs * Implement security and governance for AI/ML systems, including data privacy and safety measures * Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines * Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore, and Terraform * Apply and enforce design patterns for resilient software and agentic architectures Tasks * Bachelor’s degree in a technical field * 6+ years as Software or Solution Architect with production-scale experience * 5+ years hands-on Google Cloud experience with 2+ end-to-end enterprise implementations * 4+ years Terraform-based Google Cloud networks and security * 2+ years containerized workloads on GKE with autoscaling and observability * 2+ years CI/CD/DevSecOps with Cloud Build, GitHub Actions or Jenkins * 3+ years migration or modernization to Google Cloud * 2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including production deployment Key requirements *

advance and governance for AI/ML systems, including data privacy and safety measures * Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines * Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore, and Terraform * Apply and enforce design patterns for resilient software and agentic architectures Tasks * Bachelor’s degree in a technical field * 6+ years as Software or Solution Architect with production-scale experience * 5+ years hands-on Google Cloud experience with 2+ end-to-end enterprise implementations * 4+ years Terraform-based Google Cloud networks and security * 2+ years containerized workloads on GKE with autoscaling and observability * 2+ years CI/CD/DevSecOps with Cloud Build, GitHub Actions or Jenkins * 3+ years migration or modernization to Google Cloud * 2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, aa aaaaaA_ production deployment Key requirements *