Lead Architect, Solution Dev & Automation

Overview In this role you will lead the architectural foundation for MGA’s automation and AI-enabled product development. You’ll bridge cloud-native engineering with MGA’s ERP and data estate, moving prototypes into enterprise-ready production. You’ll shape standards and frameworks that support rapid experimentation at scale, while aligning with security and governance. This is a hands-on, leadership-forward opportunity to drive a product-centric, innovative IT culture. ResponsibilitiesDefine architectural vision, standards, and reference patterns for automation and AI-enabled product developmentTranslate technology strategy into actionable frameworks linking rapid experimentation with enterprise readinessDesign and own the automation sandbox environment with security and compliance for fast iterationManage the prototype-to-production transition pipeline with quality, security, and performance gatesOwn API strategy, microservices, data access frameworks, and cloud infrastructure designArchitect automation-enabled workflows with solution designers, data engineers, and product teamsSet standards for model deployment, vector search, data pipelines, and runtime hostingEnsure solutions integrate with ERP, CRM, eCommerce, and Data WarehouseBridge modern development practices with the enterprise IT estate and ensure security/complianceMentor full-stack developers, ML engineers, and platform engineers; develop future technical leadsPublish MGA’s Architecture Framework for AI-enabled solution development; build automation sandbox and secure accessDeliver the transition pipeline and reusable reference architectures for APIs, integrations, and workflowsLaunch multiple AI-enabled solutions across business units; establish architectural guardrails for ERP, data, integration, and cloud alignmentSupport adoption of architectural patterns and automation frameworks across the organizationImprove developer satisfaction and uplift technical capability across product teams Key requirements7–12 years in software engineering or solution architectureHands-on cloud-native development (AWS, Azure, or GCP), containers, modern app architecturesExperience deploying LLM-based apps, AI/ML systems, or enterprise automation frameworksStrong understanding of ERP, CRM, data platforms, Power Platform, and identity managementProficient in DevOps—CI/CD, Infrastructure as Code, observability, secure-by-designExperience designing vector search pipelines across multimodal dataProficiency with vector databases (Pinecone, Weaviate, pgvector) and evaluating managed vs self-hosted optionsKnowledge of data ingestion, preprocessing, and embedding refresh cycles across heterogeneous sourcesBachelor’s degree in Computer Science, Engineering, or equivalent practical experienceleadershipmentorshipcross-functional collaborationAWS, Azure, or GCP cloud platformscontainersLLM-based AI/ML deployments