Senior AI Cloud Architect
Zhone Technologies, Inc., Plano, TX, United States
Description
We are seeking a Senior AI Cloud Architect with deep expertise in AI/LLM system design and cloud-native architectures to lead the design, development, and delivery of scalable AI-powered applications. This role will play a critical part in architecting end-to-end solutions that leverage modern LLM frameworks, agentic AI, and cloud infrastructure, while partnering closely with engineering and product teams from concept through production.
Key Responsibilities: Architect, design, and deliver AI/LLM-powered cloud-native applications from initial concept through production deployment Design and implement Retrieval-Augmented Generation (RAG) pipelines, including integration with vector databases Lead architectural decisions for agentic AI systems, including deployment, orchestration, and scalability Develop and maintain architecture diagrams, technical design documents, and AI/ML white papers Build and deploy applications on Kubernetes-based cloud platforms, ensuring reliability, scalability, and security Collaborate with cross-functional teams to translate business requirements into robust technical solutions Work with large datasets, including data preparation, model training, and fine-tuning workflows Evaluate and integrate emerging AI technologies, tools, and protocols into the platform architecture Ensure best practices across cloud infrastructure, AI governance, observability, and performance optimization
Requirements 8+ years of experience in software engineering, systems architecture, or a related technical role, with significant hands-on experience designing and delivering AI/LLM-driven, cloud-native applications Senior-level experience as an Architect with a strong focus on AI / LLM development Proven experience building cloud-native applications deployed on Kubernetes Hands-on experience designing and implementing RAG pipelines and working with vector databases Experience using MCP or A2A protocols Deep understanding of Transformer-based architectures, including BERT and related models Demonstrated experience creating AI architecture and design documentation (e.g., white papers, design specs) Experience building and deploying agentic AI agents in production environments Strong background working with large datasets, including model training and fine-tuning Proven track record of delivering applications end-to-end, from design through production
Nice to Have Experience building highly scalable SaaS platforms Exposure to multi-tenant architectures and enterprise-grade AI solutions Experience working in cross-functional or distributed engineering teams
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Key Responsibilities: Architect, design, and deliver AI/LLM-powered cloud-native applications from initial concept through production deployment Design and implement Retrieval-Augmented Generation (RAG) pipelines, including integration with vector databases Lead architectural decisions for agentic AI systems, including deployment, orchestration, and scalability Develop and maintain architecture diagrams, technical design documents, and AI/ML white papers Build and deploy applications on Kubernetes-based cloud platforms, ensuring reliability, scalability, and security Collaborate with cross-functional teams to translate business requirements into robust technical solutions Work with large datasets, including data preparation, model training, and fine-tuning workflows Evaluate and integrate emerging AI technologies, tools, and protocols into the platform architecture Ensure best practices across cloud infrastructure, AI governance, observability, and performance optimization
Requirements 8+ years of experience in software engineering, systems architecture, or a related technical role, with significant hands-on experience designing and delivering AI/LLM-driven, cloud-native applications Senior-level experience as an Architect with a strong focus on AI / LLM development Proven experience building cloud-native applications deployed on Kubernetes Hands-on experience designing and implementing RAG pipelines and working with vector databases Experience using MCP or A2A protocols Deep understanding of Transformer-based architectures, including BERT and related models Demonstrated experience creating AI architecture and design documentation (e.g., white papers, design specs) Experience building and deploying agentic AI agents in production environments Strong background working with large datasets, including model training and fine-tuning Proven track record of delivering applications end-to-end, from design through production
Nice to Have Experience building highly scalable SaaS platforms Exposure to multi-tenant architectures and enterprise-grade AI solutions Experience working in cross-functional or distributed engineering teams
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