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# Senior Generative AI Technical Architect (Google Cloud)

- **Company:** Ngtalenttech Group Llc
- **Location:** United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Training Data, Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Cloud Engineering, Data Architecture, Software Design Patterns, Routing, Azure Machine Learning, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, IT Architecture, Generative AI, Agentic-AI, Data Layers, Event Driven Architecture, AI Platforms, Kubernetes, Machine Learning Operations, Google Gemini, Model Context Protocol
- **Published:** November 5, 2026
- **Apply:** https://www.dice.com/job-detail/2fa8a3ee-2688-498b-bfd3-b420d7f9d2f3

## About the Role

* 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, * 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.

## Description

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., * 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.