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).

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Required Skills