Architect, Cloud & AI Platforms

Brady Corporation is seeking an exceptional Architect - Cloud & AI Platforms to architect, build, and support our cloud and artificial intelligence infrastructure. This is a hands-on, practitioner-led role where you will directly architect solutions. You will oversee our multi-cloud strategy and enterprise AI platform architecture, primarily focused on Google Cloud Platform (GCP) and Vertex AI, alongside significant secondary infrastructure on Microsoft Azure. You will collaborate with infrastructure, software engineering, data science, and security departments to build highly available, secure, scalable, and cost-effective cloud and AI environments, deploy enterprise-grade ML models and agentic systems, migrate legacy systems, and establish best practices for multi-cloud and AI adoption across our global manufacturing and industrial operations.

• Drive the company-wide modernization agenda by establishing Infrastructure as Code (IaC) standards and architecting the GCP environment to securely support and scale Generative AI and agentic workflows.
• Architect, deploy, and operationalize enterprise AI capabilities, including Generative AI models, Retrieval-Augmented Generation (RAG) architecture, LLM fine-tuning pipelines, and agentic workflows using platform tooling such as GCP Vertex AI and Azure OpenAI Service.
• Design, build, and maintain scalable and resilient cloud environments, serving as the primary architect for our GCP environment while supporting and integrating our Azure footprint.
• Document cloud architecture and deployment diagrams, and review cloud deployments with teams to ensure adherence to standards.
• Evaluate existing legacy infrastructure and develop comprehensive, zero-downtime migration strategies primarily targeting GCP.
• Champion the use of IaC tools (e.g., Terraform, Ansible, Google Cloud Deployment Manager, Azure Resource Manager) to automate the provisioning and management of cloud resources.
• Ensure all cloud architectures meet strict industry security standards and regulatory compliance (e.g., SOC2, GDPR).
• Establish robust AI governance, data privacy, safety guardrails, and secure MLOps practices to safeguard enterprise data and prevent model drift or vulnerability exploitation.
• Design robust, unified Identity and Access Management (IAM) protocols across both GCP and Azure (Entra ID).
• Continuously monitor cloud usage and implement FinOps best practices to optimize spend across our multi-cloud environment.
• Act as a technical liaison between business units and engineering teams, and mentor team members on GCP and Azure best practices.