Google AI Architect
Overview
Design and deliver enterprise AI platforms and applications on Google Cloud using Vertex AI and Gemini while optimizing for scalability reliability security and cost. Lead cloud-native development on GKE Cloud Run Pub Sub BigQuery Cloud SQL Spanner Memorystore and Terraform. Enforce application and agentic design patterns. Implement security and governance for AI/ML systems. Architect and deliver AI solutions that drive innovation and improve client outcomes.
What You'll Do6
- 1Architect and Design: Create enterprise-grade AI applications focusing on scaling AI solutions for production with robust secure and reliable designs.
- 2LLM and AI Integration: Fine-tune Large Language Models integrate them into enterprise applications and manage deployment inference and monitoring.
- 3Enterprise Architecture: Partner with architects to align AI solutions with technical strategy governance and standards.
- 4Cloud and GenAI Native Development: Build applications using containers serverless functions and managed databases on hyperscaler platforms.
- 5Security & Governance: Protect AI/ML systems against data privacy model poisoning and adversarial attacks.
- 6Design Patterns: Apply application and agentic design patterns to build resilient systems.
Requirements11
- 1Bachelor's degree in Computer Science Engineering or related field.
- 26+ years experience as a Software or Solution Architect focused on application development and scaling production environments.
- 35+ years hands-on with Google Cloud including 2+ enterprise implementations.
- 44+ years designing and operating containerized workloads on GKE with autoscaling ingress and monitoring.
- 52+ years implementing CI/CD and DevSecOps using Cloud Build GitHub Actions or Jenkins.
- 63+ years migrating or modernizing workloads to Google Cloud through rehousing replatforming or refactoring.
- 72+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini including production deployments.
- 8Deep understanding of AI/ML concepts and LLMs in enterprise settings.
- 9Strong knowledge of security implications for AI/ML systems.
- 10Familiarity with hyperscaler tools and services.
- 11Hyperscaler Architect certification required such as AWS Certified Solutions Architect or GCP Professional Cloud Architect.
Salary Insight
$122 - $240k per year
Location
Required Skills
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