GCP AI Architect
Tasks
- Add input and output guardrails
- Apply FinOps cost optimization
- Architect Google Cloud AI platform
- Build AI safety governance frameworks
- Build Infrastructure as Code modules
- Create design doc culture with RFCs
- Create model evaluation and monitoring
- Define GKE multi cluster orchestration
- Define compute strategy for AI workloads
- Deploy model serving endpoints
- Design Vertex AI MLOps pipelines
- Design fault-tolerant distributed systems
- Ensure data sovereignty
- Implement RAG with vector search
- Implement model feature stores
- Implement policy as code
- Implement service mesh connectivity
- Integrate Gemini and PaLM models
- Lead architecture review boards
- Mentor junior architects
- Optimize training performance and throughput
- Set SLOs and error budgets
Perks/Benefits
- N/A
Skills/Tech-stack
Anthos | Autoscaling | Bias detection | BigQuery | CAP Theorem | CPU | Cloud Storage | Cloud platform | Dataflow | Distributed Systems | Drift Detection | Feature Store | FinOps | Fine Tuning | Function Calling | GKE | GPU | GRPC | Gemini | Google Cloud | Google Cloud Platform | Hallucination detection | IAM | Istio | Kpt | Kubernetes | LLM | Language Models | Large Language Models | MLOps | Machine Learning | Microservices | Model Deployment | Model Drift | Model Drift Detection | Model Evaluation | Model Serving | OPA | Open Policy Agent | PaLM | Policy Agent | Prompt engineering | PubSub | Quantization | RAG | REST | Retrieval-Augmented Generation | SRE | Spanner | Spot instances | TPU | Terraform | Vector Databases | Vector Search | Vertex AI | Vertex Feature Store
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Architect | Cloud Architect | Cloud) | Software Architect | Technical Architect
Regions
Countries
States
Cities
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