Google AI Architect
Overview
Lead architect and deliver enterprise AI platforms on Google Cloud using Vertex AI and Gemini. Architect and design scalable AI solutions while optimizing for reliability security and cost. Drive innovation through cloud-native development and modernize technology platforms.
What You'll Do11
- 1Architect and design enterprise-grade AI applications focusing on scaling for production
- 2Integrate and fine-tune large language models with emphasis on production performance
- 3Collaborate with enterprise architects to align AI solutions with technical strategy
- 4Design cloud native applications using containers serverless functions and managed databases
- 5Implement security and governance measures for AI/ML systems addressing privacy and adversarial attacks
- 6Apply agentic design patterns to build resilient software systems
- 7Lead cloud native development on GKE Cloud Run Pub Sub and other hyperscaler services
- 8Develop CI/CD pipelines using Cloud Build GitHub Actions or Jenkins
- 9Migrate modernize legacy workloads to Google Cloud through rehost replatform or refactor approaches
- 10Execute AI/GenAI projects using Vertex AI Gemini and Vector Search
- 11Provide engineering led advisory and operational capabilities through Engineering as a Service
Requirements10
- 1Bachelor's degree in Computer Science Engineering or related field
- 26+ years experience as Software or Solution Architect
- 35+ years hands-on with Google Cloud including 2+ enterprise implementations
- 44+ years designing containerized workloads on GKE
- 52+ years implementing CI/CD and DevSecOps practices
- 63+ years migrating to Google Cloud platforms
- 72+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini
- 8Hyperscaler Architect certification required
- 9Ability to travel up to 50% based on client needs
- 10Strong understanding of AI/ML concepts and security implications
Salary Insight
$122 - $240k per year
Location
Required Skills
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