AI Architect

Job Title : AI Architect Location : Atlanta, GA (Onsite – Hybrid)Job Description : Role SummaryLead the design and delivery of AIML and GenAI solutions across broker operationsincluding placement quoting underwriting support claims advocacy and client servicingDrive AI integration across Azure Databricks Python ML and legacy NET systems to modernise broker workflows and enhance decisionmaking productivity and client experienceKey ResponsibilitiesEngineer autonomous secure agentsSet up agent evaluation automationArchitect endtoend AIML GenAI solutions from design to productionTranslate broker use cases submission triage quote comparison document ingestion IDP recommendation engines agent assist client insightsDefine enterprise AI patterns standards and reusable componentsEnsure scalability performance explainability compliance and cost efficiencyLead technical governance design reviews and stakeholder engagementDesign data ML platforms on Azure DatabricksEmbed AI into broker platforms placement quoting CRM document systems NET appsUnderstand the insurance domain and design and implement extensible evolvable schemasPrimary Skills MustHaveAIML GenAIStrong ML lifecycle expertise and GenAI design RAG prompting retrieval evaluationAbility to choose optimal approach ML vs GenAI based on business needGenAI agentic engineering experience with agentic frameworksoContext management MCP elicitation notification patterns MCPA2A protocols CodeAct Code Interpreter Agent Skill evaluationmanagement Agent harness and RAGAgent evaluation expertise including automation of evaluation workflowsEngineering Agent Skill working alongside Insurance SMEsPython Agent EngineeringAdvanced Python solutioning for production AI and agent systemsProficient in agentic frameworks and productiongrade agent design including multiagent patternsHumanintheloop HITL workflow and interaction design for agent systemsAbility to leverage coding agents and specdriven development across all SDLC phasesExperience with containers for scalable portable deployment of AI and agent workloadsAzure Data PlatformAzure solutions architecture across AI data integration security CICD and observabilityHandson with enterprise Azure services for AIdata platforms and secure application integrationSecurity engineering for agents and platforms including OAuth2 Azure permissions IAM policies and finegrained access control FGACExperience with credentials and secrets management for enterprise AI systemsFamiliarity with infrastructure as Code using Terraform for Azure environment provisioning and platform standardizationAbility to implement scalable resilient and costefficient architecture for enterprise AI solutionsIntegration APIsStrong integration skills with REST APIs webhooks and APIled eventdriven integration with enterprise systemsExpertise with relational NoSQL and graph databasesSecondary SkillDatabricks Lakehouse PreferredExperience with Delta Lake ETLELT feature engineering and job orchestrationExperience creating finetuning datasets for domainspecific AI use casesExperience with domainspecialized model finetuning for insurance and broker workflowsBroker Domain Knowledge PreferredUnderstanding of wholesale insurance and broker workflows submissions placement quoting renewals and client servicingAbility to map AI to outcomes such as placement speed hit ratio productivity and client retentionUnderstand the insurance domain and design and implement extensible evolvable schemas and ontologiesDifferentiatorsAI integration in legacyNET broker platformsMLOps model governance and drift monitoringSecurity compliance PII handling auditabilityRealtimeeventdriven architectures for trading workflowsAnalytics dashboards for broker performance and AI impactOutcome FocusFaster placement cycles and improved quote qualityIncreased broker productivity and automation STPBetter client insights and retention