Role Purpose<\/p>\n
\tLead the design, build, and deployment of production-grade AI solutions on Microsoft Azure. Own end-to-end delivery\u2014from data pipelines to model deployment, ensuring security, reliability, and compliance.<\/p>\n
Responsibilities<\/p>\n
\tDesign and implement AI solutions using Azure AI services (OpenAI, AI Search, Machine Learning).
\n\tDevelop secure APIs and integrate with enterprise systems using Azure API Management and Event Hub.
\n\tContainerize workloads and deploy to AKS, App Service, or Functions with CI\/CD pipelines.
\n\tEnsure observability, performance tuning, and cost optimization for AI workloads.
\n\tCollaborate with cross-functional teams and document architecture, runbooks, and best practices.
\n\tAzure AI & ML: Azure OpenAI Service, AI Studio, AI Search, Azure Machine Learning.
\n\tData & Integration: Data Lake Storage, Synapse\/Fabric, Data Factory, Event Hub, API Management.
\n\tCompute & Hosting: AKS, Azure Functions, App Service; IaC with Bicep\/ARM\/Terraform.
\n\tDevOps\/MLOps: Azure DevOps or GitHub Actions, MLflow integration, telemetry dashboards.
\n\tLanguages: Python (required), plus C#\/.NET or TypeScript\/Node; LangChain or Semantic Kernel preferred.
\n\t7+ years in software\/ML engineering, with 3+ years delivering production AI solutions on Azure.
\n\tProven track record of shipped solutions with architecture diagrams and runbooks.
\n\tExpertise in RAG system design, prompt engineering, and performance optimization.
\n\tStrong data engineering skills and secure integration patterns.
\n\tApplied knowledge of Responsible AI principles and compliance requirements.
\n\tOutcome-oriented with strong problem-solving skills.
\n\tExcellent communication and stakeholder management abilities.
\n\tCollaborative leadership and mentoring capability.
\n\tAdaptability to ambiguity and incremental delivery approaches.
\n\tExperience with Microsoft Fabric and Databricks on Azure.
\n\tDomain experience in financial services.
\n\tAzure AI Engineer Associate certification or equivalent.<\/p>\n
Core Tech Stack<\/p>\n
\tAzure AI & ML: Azure OpenAI Service, AI Studio, AI Search, Azure Machine Learning.
\n\tData & Integration: Data Lake Storage, Synapse\/Fabric, Data Factory, Event Hub, API Management.
\n\tCompute & Hosting: AKS, Azure Functions, App Service; IaC with Bicep\/ARM\/Terraform.
\n\tDevOps\/MLOps: Azure DevOps or GitHub Actions, MLflow integration, telemetry dashboards.
\n\tLanguages: Python (required), plus C#\/.NET or TypeScript\/Node; LangChain or Semantic Kernel preferred.<\/p>\n
Required Experience<\/p>\n
\t7+ years in software\/ML engineering, with 3+ years delivering production AI solutions on Azure.
\n\tProven track record of shipped solutions with architecture diagrams and runbooks.
\n\tExpertise in RAG system design, prompt engineering, and performance optimization.
\n\tStrong data engineering skills and secure integration patterns.
\n\tApplied knowledge of Responsible AI principles and compliance requirements.<\/p>\n
Nice-to-Have<\/p>\n
\tExperience with Microsoft Fabric and Databricks on Azure.
\n\tDomain experience in financial services.
\n\tAzure AI Engineer Associate certification or equivalent.<\/p>\n
Qualifications<\/p>\n
\tDegree in Computer Science\/Engineering\/Math or equivalent industry experience.<\/p>\n
go to method of application \u00bb<\/p>\n
Apply via company website ( ) or<\/p>\n
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