Google AI Architect, Vertex AI & Gemini
Overview
Own the architecture and delivery of enterprise AI platforms on Google Cloud using Vertex AI and Gemini. You will drive production-scale AI solutions, integrating LLMs, RAG, and agentic patterns into mission-critical operations. Collaborate with cross-functional teams to modernize data platforms and enforce security and governance. This role stands out for its focus on end-to-end AI architecture, from data pipelines to deployment, within a leading consultancy.
What You'll Do7
- 1Architect and deliver enterprise AI platforms on Google Cloud with Vertex AI and Gemini, optimizing for scale, security, and cost.
- 2Design and fine-tune LLM solutions, implementing prompt engineering, safety policies, and Vector Search for production.
- 3Build RAG and agentic systems using Vertex AI Vector Search and BigQuery vector, with context management and observability.
- 4Define end-to-end architectures covering data pipelines, model lifecycle, APIs, and CI/CD with Vertex AI Pipelines and Cloud Build.
- 5Lead cloud-native development on GKE, Cloud Run, Pub/Sub, and Terraform, enforcing design patterns.
- 6Implement security and governance for AI systems, addressing data privacy, model poisoning, and adversarial attacks.
- 7Collaborate with enterprise architects to align AI solutions with company strategy and standards.
Requirements10
- 16+ years as a Software or Solution Architect, focusing on application development and scaling for production.
- 25+ years hands-on with Google Cloud, including 2+ end-to-end enterprise implementations.
- 34+ years designing GCP networks, security, and landing zones with Terraform.
- 42+ years operating containerized workloads on GKE (autoscaling, ingress, monitoring).
- 52+ years implementing CI/CD with Cloud Build, GitHub Actions, or Jenkins.
- 63+ years executing migration or modernization to Google Cloud.
- 72+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including 1+ years production (RAG, safety policies).
- 8Deep understanding of AI/ML concepts and LLMs in enterprise settings.
- 9Hyperscaler Architect certification (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert, or GCP Professional Cloud Architect).
- 10Ability to travel up to 50% based on client needs.
Salary Insight
$122 - $240k per year
Location
Required Skills
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