Job TitleJob DescriptionKey Responsibilities1. Multi-Cloud Architecture & GovernanceDefine and implement cloud-agnostic architecture patterns across AWS and GCPStandardize GCP governance aligned to AWS controlsEstablish reusable reference architectures for data, AI, and infrastructurePromote abstraction via:Containers (Kubernetes)APIsInfrastructure as Code (Terraform)2. Hands-On Enablement (POCs & Pipeline Delivery)Build proof-of-concept solutions to validate architecture patternsDevelop 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 adoptionTranslate architecture into working, scalable solutions3.
AI Integration & MLOps EnablementDesign and implement AI-ready pipelines (structured + unstructured data)Support:Model integration into enterprise workflowsMLOps lifecycle enablement (CI/CD, monitoring, governance)AI tool/vendor evaluationMature organization from:POCs ? Embedded AI ? Governed enterprise AI4.
Data Architecture & Integration (CMDB/APM-Aligned)Architect data flows integrating:ServiceNow (CMDB/APM)Apptio (cost transparency)Jira (delivery data)Address key challenges:Data latencyData duplicationCost visibility gapsEnforce system-of-record and data ownership principles5. Governance & FinOps (Advisory + Enablement)Define standards for:Cloud cost optimization (FinOps)AI governance and lifecycle managementData quality and pipeline SLAsSupport KPI transparency:Cloud cost per applicationData pipeline reliabilityAI ROIGuide teams while enabling them through working solutions6. Platform Strategy & Shared Services LeadershipAct as a central architecture leader and enablerSupport teams through:Architecture reviewsPOC deliveryDesign guidanceBuild reusable enterprise assets:PatternsTemplatesIntegration frameworksRequired Experience7+ years in cloud architecture, data engineering, or infrastructureProven experience in multi-cloud environments (AWS + GCP)Demonstrated ability to:Design architecture and deliver working solutionsBuild data pipelines and integrationsStrong experience with:Python, SQLETL/ELT pipelinesInfrastructure as Code (Terraform preferred)Containers (Kubernetes)AI & Modern Architecture RequirementsHands-on experience with:AI/ML integration into enterprise pipelinesMLOps or AI lifecycle toolingExperience evaluating and implementing:AI platformsAutomation toolingPreferred ExperienceServiceNow CMDB/APM integrationApptio (cost allocation / FinOps)Experience solving:Cross-system duplicationData lineage challengesExposure to Generative AI integrationSuccess Metrics (Aligned to Your KPIs)Reduction in cloud cost per applicationImprovement in pipeline SLAsReduction in duplicate data/integrationsIncrease in production AI-enabled workflowsAdoption of multi-cloud architecture standardsNumber of successful POCs transitioned to production