AI Platform Architect

Position Title: Onshore AI Platform Architect

Location: Milpitas, CA (Onsite)

Employment: Full time
Experience: 12+ Yrs total/ 7+ Yrs Cloud, 5+ Yrs AI Platform

KEY RESPONSIBILITIES:

• Define enterprise AI platform strategy, reference architectures, AI landing zones, and platform blueprints across Azure and Google Cloud Platform.
• Architect AI infrastructure: GPU clusters, Kubernetes (AKS/GKE), model training & inference platforms, vector databases, and feature stores.
• Design and operate Azure AI Foundry, Azure OpenAI, Azure ML, Google Vertex AI, and Gemini-based GenAI services.
• Establish enterprise MLOps and LLMOps frameworks—CI/CD pipelines, automated model training, deployment, evaluation, and rollback.
• Build GenAI patterns for RAG, agentic AI, and secure integration of enterprise data with LLMs (OpenAI, Vertex, Gemini, open-source models).
• Implement AI security and governance: identity (Entra ID / Google IAM), RBAC, private networking, Key Vault / Secret Manager, and Responsible AI controls.
• Automate platform provisioning via Terraform, Bicep, and GitOps; drive cost optimization and policy-driven governance.
• Design AI observability—model performance, drift, GPU utilization, and prompt/response monitoring using Azure Monitor and Cloud Operations.
• Advise executives and technical teams; lead architecture workshops, roadmaps, and mentor platform engineers.

 REQUIRED TECHNICAL SKILLS:

AI Platforms & Cloud

• Azure AI Foundry, Azure OpenAI, Azure ML
• Google Vertex AI, Model Garden, Gemini
• Microsoft Azure + Google Cloud (multi-cloud)

 MLOps / LLMOps & Automation

• Azure ML & Vertex AI Pipelines, MLflow, Kubeflow
• Terraform, Bicep, GitHub Actions, Azure DevOps
• Python, PowerShell, Bash, YAML

Containers & Infra

• Kubernetes, AKS, GKE, Docker, Registries

GPU compute, model serving, vector DBs, RAG

Security & Governance

• Entra ID, Google IAM, RBAC, Key Vault, Secret Manager

Defender for Cloud, Security Command Center, Responsible AI

REQUIRED QUALIFICATIONS:

• Bachelor’s degree in computer science, Engineering, IT, or related field.
• 12+ years of infrastructure/cloud/platform experience, including 7+ years in cloud architecture and 5+ years designing enterprise AI/ML platforms.
• Proven hands-on delivery of Azure AI and Google Vertex AI environments, including GPU and Kubernetes-based AI platforms.