> Markdown version of [/jobs/ext/4321344-senior-generative-ai-technical-architect](https://www.wearedevelopers.com/jobs/ext/4321344-senior-generative-ai-technical-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Generative AI Technical Architect

- **Company:** Laiba Technologies LLC
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Training Data, Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Engineering, Software Design Patterns, Graph Database, Routing, Azure Machine Learning, Google Cloud, Chatbots, 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
- **Published:** October 31, 2026
- **Apply:** https://www.dice.com/job-detail/e4a99ecb-6375-4bbf-84b4-9c31bc3cc75e

## 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:

 * Gemini, Vertex AI, Agent Builder
 * Agentic AI and Multi-Agent Systems
 * RAG, Vector Databases, Knowledge Graphs
 * AI Gateway and Model Routing
 * AI Observability and Monitoring
 * Semantic Layer Architecture
 * MLOps, LLMOps, and AI Governance
 * Kubernetes, APIs, Event-Driven Architectures

## Description

* 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:

 * AI Gateway / Model Gateway architectures
 * Agentic and conversational AI platforms
 * RAG and knowledge-based AI solutions
 * Semantic data layers and AI-ready data architectures
 * 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.