Google AI Architect
Overview
Lead architect enterprise AI platforms on Google Cloud focusing on scalability reliability security and cost. Drive innovation through cloud native development and AI integration. Shape technical strategy and lead cross functional teams.
What You'll Do11
- 1Architect and deliver enterprise AI platforms and applications on Google Cloud using Vertex AI and Gemini
- 2Design fine tune evaluate and govern LLM solutions with Gemini on Vertex AI
- 3Implement RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector
- 4Define end-to-end architectures across data pipelines feature engineering model lifecycle APIs/microservices and CI/CD/MLOps/LLMOps
- 5Lead cloud native development on GKE Cloud Run Pub Sub BigQuery Cloud SQL Spanner Memorystore and Terraform
- 6Implement security and governance for AI/ML systems addressing data privacy model poisoning and adversarial attacks
- 7Apply and enforce Application Design Patterns and Agentic Design Patterns
- 8Collaborate with enterprise architects to align AI solutions with technical strategy governance and standards
- 9Develop and operate containerized workloads on GKE with autoscaling ingress monitoring and observability
- 10Ship scalable reliable secure and cost optimized AI platforms
- 11Drive transformation of technology platforms accelerating digital ventures and client growth
Requirements11
- 1Bachelor's degree in Computer Science Engineering or related field
- 26+ years experience as Software or Solution Architect focusing on application development and scaling production solutions
- 35+ years hands on Google Cloud including 2+ end-to-end enterprise implementations
- 44+ years designing and implementing Google Cloud networks security controls and landing zones using Terraform
- 52+ years building and operating containerized workloads on GKE with autoscaling ingress monitoring and observability
- 62+ years implementing CI/CD and DevSecOps with Cloud Build GitHub Actions or Jenkins
- 73+ years migrating or modernizing workloads to Google Cloud including rehost replatform refactor
- 82+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini including production deployment
- 9Deep understanding of AI/ML concepts including LLMs and enterprise applications
- 10Strong security awareness regarding AI/ML systems data privacy model poisoning and adversarial attacks
- 11Familiarity with hyperscaler tools and services
Salary Insight
$122 - $240k per year
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