Senior Generative AI Technical Architect (Google Cloud) Role Summary We are seeking a Senior Generative AI Technical Architect to define and lead the enterprise AI foundation architecture within the Google Cloud ecosystem. The ideal candidate will have hands-on experience building scalable GenAI platforms, agentic AI solutions, AI gateways, observability frameworks, and semantic data architectures that enable enterprise-wide AI adoption.

Key Responsibilities

• Define enterprise AI architecture, standards, and reusable design patterns.
• Architect GenAI and Agentic AI solutions using Vertex AI, Gemini, Agent Builder, and Google Cloud Platform services.
• Design and implement:  o AI Gateway / Model Gateway architectures o Agentic and conversational AI platforms o RAG and knowledge-based AI solutions o Semantic data layers and AI-ready data architectures o AI observability, monitoring, and governance frameworks
• Establish enterprise AI platform capabilities including security, scalability, model governance, and responsible AI.
• Build AI delivery frameworks, MLOps/LLMOps pipelines, and reusable accelerators.
• Partner with business, engineering, data, and product teams to drive AI strategy and execution.

Required Qualifications

• 12+ years of technology and architecture experience.
• 5+ years in cloud architecture and AI/ML platforms.
• 3+ years focused on Generative AI and LLM architectures.
• Proven experience designing foundational AI architectures on Google Cloud Platform (Google Cloud Platform).
• Expertise in:  o Gemini, Vertex AI, Agent Builder o Agentic AI and Multi-Agent Systems o RAG, Vector Databases, Knowledge Graphs o AI Gateway and Model Routing o AI Observability and Monitoring o Semantic Layer Architecture Classification: Internal o MLOps, LLMOps, and AI Governance o Kubernetes, APIs, Event-Driven Architectures

Preferred Qualifications

• Google Cloud Professional Cloud Architect certification.
• Experience with MCP (Model Context Protocol), AI delivery factories, and enterprise AI platform modernization.
• Experience establishing AI governance, responsible AI practices, and enterprise-scale GenAI operating models.