Google AI Architect
San DiegoLast seen today
Summary
Design and architect enterprise-grade AI applications on Google Cloud, with deep expertise in LLMs, Gemini, and Vertex AI. Lead end-to-end solution design across data pipelines, model lifecycle, cloud infrastructure, and MLOps/LLMOps. Implement RAG and agentic solutions, enforce security and governance for AI/ML systems, and guide cloud-native development on GKE, Cloud Run, and related Google Cloud services. Requires 6+ years as a software/solutions architect, 5+ years hands-on GCP, 2+ years production Vertex AI/Gemini experience, and a hyperscaler architect certification.
CybersecurityData ScienceAIAWSAzureDockerKubernetesSQLTerraformAdversarial AttacksAgentic AIAgentic Design PatternsApplication Design PatternsAWS Certified Solutions ArchitectAzure Solutions Architect ExpertBigqueryCI CDCloud BuildCloud RunCloud SpannerCloud SQLData PrivacyDevsecopsEnterprise ArchitectureFunction CallingGCP Professional Cloud ArchitectGeminiGitHub ActionsGkeGoogle Cloud Platform GCPInference OptimizationJenkinsLLM Large Language ModelsLlmopsMachine LearningMemorystoreMicroservicesMlopsModel EvaluationModel PoisoningPrompt EngineeringPub SubRAG Retrieval Augmented GenerationSafety PoliciesServerlessTool CallingVector SearchVertex AIVertex AI Pipelines