AI Architect

This role is responsible for setting how AI systems are designed, built, governed and scaled – ensuring solutions are secure, reliable, cost-efficient and deeply embedded into business workflows. You will partner closely with Engineering, Product Management, Data and Operations leadership to identify high-impact use cases and deliver AI capabilities that drive measurable improvements across pricing, capacity matching, customer service, claims, risk and operator productivity. What you’ll be doing: AI Strategy & Enterprise ArchitectureEvaluate and recommend AI models, APIs and platforms (e.g., Anthropic, OpenAI, Microsoft, Google) based on security, reliability, cost and enterprise fitDefine the enterprise AI architecture across Azure OpenAI, Azure AI Search, Microsoft Fabric, Azure ML, APIs, event-driven systems and operator-facing toolsEstablish standards for building LLM applications, retrieval-augmented generation (RAG) systems, intelligent agents and ML models at scaleCreate reference architectures for AI-powered solutions including real-time workflows, automation, copilots and knowledge assistantsApplication Architecture & IntegrationDesign how AI services integrate with core applications, including broker tools, APIs, workflows and backend servicesEstablish patterns for serverless functions, microservices, REST APIs, event-driven pipelines and end-to-end orchestrationPartner with application development teams to embed AI into product features with the right performance, security, authentication and data flow patternsEnsure AI solutions meet enterprise CI/CD, observability, reliability and SLA standardsSolution Design & Technical LeadershipLead solution designs for AI platforms including vector databases, embedding pipelines, inference services, feature stores and model registriesTranslate complex operator workflows into scalable, AI-enabled architectures that improve decision-making and productivityConduct architecture, design reviews and mentor AI Engineers, Software Engineers, Data Engineers and Data ScientistsData & Integration ArchitecturePartner with Data Engineering to ensure Fabric Lakehouse, Delta tables, warehouse layers and streaming systems support both training and inference workloadsArchitect and optimize RAG pipelines using Azure AI Search, vector indexing, embeddings and metadata strategiesMLOps, Governance & Operational ReadinessDefine and implement enterprise MLOps standards for model lifecycle management, versioning, monitoring and retrainingApply Responsible AI practices including content filtering, privacy, compliance and hallucination mitigationEnsure AI systems are observable with performance and cost monitoringInnovation & Continuous ImprovementEvaluate emerging AI models, agent frameworks and Azure capabilities for use in logistics workflowsLead proofs of concept (PoCs) and accelerate adoption of high-value AI initiativesDevelop reusable technical playbooks and architectural patterns to mature AI across engineering teams Employment visa sponsorship is unavailable for this position.

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