Question
10+

Senior AI Cloud Architect

2/4/2026

The Senior AI Cloud Architect will lead the design, development, and delivery of scalable AI-powered applications, focusing on architecting end-to-end solutions utilizing modern LLM frameworks and agentic AI. Key duties include designing RAG pipelines, leading architectural decisions for agentic AI systems, and building/deploying applications on Kubernetes-based cloud platforms.

Working Hours

40 hours/week

Company Size

501-1,000 employees

Language

English

Visa Sponsorship

No

About The Company
DZS is a global leader of Network Edge, Connected Home/Enterprise and AI Cloud Software solutions that enable gigabit broadband everywhere. Headquartered in Plano, Texas, with offices in Australia, Canada, Germany, and UAE, DZS serves over 200 active customers in countries across the Americas, Europe/Middle East/Africa, and Australia/New Zealand. Communications service providers (CSPs) rely on our systems, platforms, and services to connect millions of homes and businesses. More than half of the top 25 telecom providers in the markets we serve depend on DZS for fixed and wireless access, home/enterprise connectivity, converged broadband, and AI-driven cloud automation, orchestration and insights.
About the Role

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


Key Skills
AI/LLM System DesignCloud-Native ArchitecturesRetrieval-Augmented Generation (RAG)Vector DatabasesAgentic AIKubernetesData PreparationModel TrainingFine-TuningArchitecture DiagramsTechnical Design DocumentsAI GovernanceTransformer ArchitecturesBERTScalabilitySecurity
Categories
TechnologyEngineeringSoftwareData & Analytics
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