Job description

Job Type: Contract Job Category: IT Job Description Job Title: Azure Platform Architect with AI/ML Job Summary: We are seeking an experienced Azure Platform Architect / Engineer to design, implement, and manage scalable AI/ML cloud architectures. The ideal candidate will have expertise in Azure services, Gen AI integration, cross-cloud platform implementation, Infrastructure as Code (IaC), MLOps, security, and DevOps. Key Responsibilities: Azure Platform Architecture • Design and implement scalable, secure, and cost-effective AI/ML architectures using Azure. • Utilize AWS services such as EKS, Azure Lambda, and Azure Step Functions for serverless and container-based AI/ML applications. • Implement data pipelines and big data processing using Amazon S3, AWS Glue, and Amazon EMR. Gen AI & AI/ML Integration • Lead the design and implementation of AI/ML pipelines integrating with Azure SageMaker and Amazon Bedrock. • Develop and optimize ML models using Amazon Rekognition, Comprehend, Forecast, and Personalize. • Implement MLOps practices for model versioning, automated testing, and continuous deployment. • Utilize Amazon Bedrock to create foundation models and build generative AI applications. Cross-Cloud Platform Implementation • Design and implement hybrid AI solutions across Azure, and Google Cloud. • Develop integration strategies for seamless data flow and model deployment across multiple cloud environments. • Implement multi-cloud governance and security best practices. Infrastructure as Code (IaC) • Develop and maintain Terraform code for Azure infrastructure provisioning and third-party AI services integration. • Implement modular and reusable Terraform configurations for AI/ML environments. • Utilize Terraform to manage complex AI/ML infrastructure, including GPU-enabled instances and distributed training clusters. AWS Administration & Security • Manage Azure resources for AI workloads, including EC2 GPU instances, SageMaker notebooks, and EKS clusters. • Implement robust security for AI/ML workloads using data encryption, IAM policies, and secure deployment practices. • Set up monitoring and alerting using AWS CloudWatch, Datadog, and Splunk. CI/CD & DevOps • Configure and customize CI/CD pipelines for AI/ML model deployment and Terraform infrastructure automation. • Integrate GitLab with CI/CD tools for AI model and infrastructure deployment. • Implement GitOps practices for managing AI infrastructure deployments. Collaboration & Documentation • Utilize GitLab for version control, code reviews, and AI/ML model development. • Document AI/ML pipelines, architectures, and infrastructure in Confluence for team collaboration. Qualifications: • 5+ years of hands-on experience designing and implementing AI/ML platforms on Azure. • Expertise in Azure AI services such as Amazon Bedrock, SageMaker, Rekognition, Comprehend, and Personalize. • Strong experience in cross-cloud platform implementation (AWS, Azure, Google Cloud). • Proficiency in Terraform, GitLab, and CI/CD for AI/ML workloads. • Strong Python programming skills for ML model development. • Knowledge of containerization (Docker, Kubernetes, EKS). • Excellent problem-solving and communication skills. • Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field (or equivalent experience). #AzurePlatformArchitect #AI #ML #ArtificialIntelligence #MachineLearning #CloudComputing #MicrosoftAzure #TechnologyJobs #DataScience #USJobs #TechCareers #ITJobs #CareerOpportunities #JobSearch #ComputationalIntelligence #CloudSolutions #BigDataAnalytics Required Skills Performance Architect

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