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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Cloud Architect - **Company:** NorthMark Strategies - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computing Platforms, Microsoft Azure, Cloud Computing, Cloud Engineering, Cyber Security, Data Infrastructure, Data Security, Domain Name System (DNS), Network Topologies, InfiniBand, Job Scheduling, Peering, Cloud Services, Azure Machine Learning, Policy as Code, Cloud Platform System, Delivery Pipeline, Multi-Cloud, Kubernetes, Information Technology, AWS Data Analytics, Machine Learning Operations, Hardware Infrastructure, Model Inference, Terraform, Automation Anywhere, Devsecops - **Published:** October 26, 2026 - **Apply:** https://www.dice.com/job-detail/3bfb2237-c85a-4808-a57b-a65db68a8861 ## About the Role * Production depth across AWS and Azure: landing zones, multi-account/subscription governance, managed services, and security architectureManaged Kubernetes at scale (AKS, EKS), including cluster lifecycle management and workload schedulingCloud networking: hub-and-spoke topologies, peering, private DNS, private endpoints, and hybrid connectivityTerraform fluency in complex, multi-account environments * A track record of designing and enforcing cloud governance: guardrails, policy-as-code, and compliance controls * Influencing engineering teams and senior stakeholders without direct authority * Clearly communicating architecture decisions and trade-offs, both written and presented Certifications (one or more expected) * Microsoft Certified: Azure Solutions Architect Expert * AWS Certified Solutions Architect (Associate or Professional) Preferred * Cloud HPC for scientific or engineering workloads, including job schedulers and high-speed interconnects (e.g., InfiniBand) * Cloud data platform delivery at production scale (e.g., medallion architecture, AWS data services) * AI inference gateway or model serving infrastructureAgentic AI workflows applied to infrastructure engineering * GPU infrastructure or ML platforms in the cloudRegulated or high-availability environments (e.g., financial services, motorsport, government) * A degree in Engineering, Computer Science, or a related field, or equivalent experience * CCNA or equivalent network engineering foundation What the Role is This is a senior individual-contributor role focused on public cloud architecture. You will set platform direction and standards, and engineering teams will deliver against them. You'll work closely with the Director of Cloud Platform, who owns team management, operating model, budget, and program delivery, while you make technical decisions. Hands-on credibility matters: you'll work directly in infrastructure as code and step in on critical issues when needed. It is impossible to list every requirement for, or responsibility of, any position. Similarly, we cannot identify all the skills a position may require since job responsibilities and the Company's needs may change over time. Therefore, the above job description is not comprehensive or exhaustive. The Company reserves the right to adjust, add to or eliminate any aspect of the above description. The Company also retains the right to require all employees to undertake additional or different job responsibilities when necessary to meet business needs. Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future. ## Description We are looking for a Senior Cloud Architect to own the technical direction of our public cloud platforms. Reporting to the Director of Cloud Platform, you will be the senior technical authority across AWS and Azure. You will set architecture standards, design governance controls, and guide engineering teams in turning them into production-grade platforms. The role spans the full architecture lifecycle. That covers discovery and design, implementation guidance, platform operationalization, and the documentation and enablement that let platforms scale beyond the people who built them. You will work across managed Kubernetes, cloud networking, security, and data platform architecture. You will also shape how AI tooling is embedded in engineering: not as a productivity add-on, but as a quality gate in the delivery pipeline. Requirements Architecture Standards & Governance * Define cloud architecture standards, reference architecture, and design principles across AWS and Azure * Design and enforce technical guardrails across multi-account AWS and multi-subscription Azure environments, using policy-as-code and compliance controls (e.g., AWS SCPs/RCPs, Azure Policy) * Translate industry frameworks (e.g., CAF, Well-Architected) into concrete technical controls and patterns * Design the tagging and cost-attribution architecture that underpins FinOps reporting * Present architecture direction, trade-offs, and technical risk to senior leadership alongside the Director Platform Architecture * Architect multi-cloud landing zones and hub-and-spoke network topologies across AWS and Azure * Design Kubernetes platforms at scale on managed services (e.g., AKS, EKS), including cluster lifecycle, multi-tenancy, and workload scheduling * Lead cloud network architecture: inter-region and cross-cloud routing, private DNS, private endpoints, and connectivity to corporate networks (e.g., ExpressRoute, Direct Connect) * Integrate batch and workflow orchestration on Kubernetes with cloud-native service networking and modern workload identity patterns Data Platform Architecture * Design cloud data platforms using layered (e.g., medallion) architecture across ingestion, transformation, and consumption * Enable distributed querying across curated data sources for engineering and analytical users * Define data access control, governance, and observability patterns AI & Emerging Capabilities * Architect AI inference gateway infrastructure that provides centralized model routing, security controls, cost attribution, and observability * Design self-hosted, open-weight model inference on cloud GPU capacity, so AI workloads can run against sensitive data without exposure to third-party model providers * Design agentic AI workflows for engineering (deployment review, IaC PR validation, platform operations) that act as quality gates in the delivery pipeline Technical Leadership & Enablement * Serve as the technical escalation point for the hardest platform problems * Mentor engineers through design reviews, pairing, and architecture guidance * Run technical workshops on new architecture patterns, tools, and practical AI workflows * Contribute to technical interviews and set the technical bar for platform roles Technical Delivery * Own Infrastructure as Code standards (Terraform), including bringing existing cloud resources under version-controlled IaC and enforcing repeatable deployment patterns * Define DevSecOps pipeline patterns and identity and security architecture * Produce architecture documentation (high-level and low-level designs) and runbooks that let others operate and extend the platforms