AI & Multi-Cloud Architecture
Title- AI & Multi-Cloud Architecture Lead (Hands-On)Location- Juno Beach, FL - Onsite(Architecture + Enablement + Proof Delivery)Role SummaryResponsible for defining and advancing a cloud-agnostic, AI-enabled architecture strategy that supports enterprise analytics, automation, and operational decision-making across multi-cloud environments. This role leads architecture standards and governance across AWS and GCP while actively delivering hands-on prototypes, data pipelines, and AI integrations to accelerate adoption.Operating as a shared services architecture function, this role both guides and demonstrates best practices—bridging strategy and execution to ensure scalable, cost-efficient, and production-ready solutions aligned with ServiceNow CMDB/APM and Apptio models.Core Role IdentityDimension ExpectationArchitecture Defines standards, patterns, governanceDelivery Builds POCs, pipelines, and AI integrationsModel Shared service / enterprise enablementAuthority Influences + demonstrates (not just advises)Cloud Multi-cloud, cloud-agnostic mindsetKey Responsibilities1. Multi-Cloud Architecture & Governance• Define and implement cloud-agnostic architecture patterns across AWS and GCP• Standardize GCP governance aligned to AWS controls• Establish reusable reference architectures for data, AI, and infrastructure• Promote abstraction via:o Containers (Kubernetes)o APIso Infrastructure as Code (Terraform)2. Hands-On Enablement (POCs & Pipeline Delivery)• Build proof-of-concept solutions to validate architecture patterns• Develop and optimize data pipelines and integrations across systems (ServiceNow, Apptio, Jira)• Implement AI-enabled workflows (model integration, automation)• Provide hands-on support to delivery teams to accelerate adoption• Translate architecture into working, scalable solutions3. AI Integration & MLOps Enablement• Design and implement AI-ready pipelines (structured + unstructured data)• Support:o Model integration into enterprise workflowso MLOps lifecycle enablement (CI/CD, monitoring, governance)o AI tool/vendor evaluation• Mature organization from:o POCs → Embedded AI → Governed enterprise AI4. Data Architecture & Integration (CMDB/APM-Aligned)• Architect data flows integrating:o ServiceNow (CMDB/APM)o Apptio (cost transparency)o Jira (delivery data)• Address key challenges:o Data latencyo Data duplicationo Cost visibility gaps• Enforce system-of-record and data ownership principles5. Governance & FinOps (Advisory + Enablement)• Define standards for:o Cloud cost optimization (FinOps)o AI governance and lifecycle managemento Data quality and pipeline SLAs• Support KPI transparency:o Cloud cost per applicationo Data pipeline reliabilityo AI ROI• Guide teams while enabling them through working solutions6. Platform Strategy & Shared Services Leadership• Act as a central architecture leader and enabler• Support teams through:o Architecture reviewso POC deliveryo Design guidance• Build reusable enterprise assets:o Patternso Templateso Integration frameworksRequired Experience• 7+ years in cloud architecture, data engineering, or infrastructure• Proven experience in multi-cloud environments (AWS + GCP)• Demonstrated ability to:o Design architecture and deliver working solutionso Build data pipelines and integrations• Strong experience with:o Python, SQLo ETL/ELT pipelineso Infrastructure as Code (Terraform preferred)o Containers (Kubernetes)AI & Modern Architecture Requirements• Hands-on experience with:o AI/ML integration into enterprise pipelineso MLOps or AI lifecycle tooling• Experience evaluating and implementing:o AI platformso Automation toolingPreferred Experience• ServiceNow CMDB/APM integration• Apptio (cost allocation / FinOps)• Experience solving:o Cross-system duplicationo Data lineage challenges• Exposure to Generative AI integrationSuccess Metrics (Aligned to Your KPIs)• Reduction in cloud cost per application• Improvement in pipeline SLAs• Reduction in duplicate data/integrations• Increase in production AI-enabled workflows• Adoption of multi-cloud architecture standards• Number of successful POCs transitioned to production