Job Type: Contract

Job Category: IT

Job Description

Job Title: AWS Platform Architect  With AI ML 

Location: Charlotte, NC & Atlanta, GA

Job Summary:

We are seeking an experienced AWS Platform Architect / Engineer to design, implement, and manage scalable AI/ML cloud architectures. The ideal candidate will have expertise in AWS services, Gen AI integration, cross-cloud platform implementation, Infrastructure as Code (IaC), MLOps, security, and DevOps.

Key Responsibilities:

AWS Platform Architecture

• Design and implement scalable, secure, and cost-effective AI/ML architectures using AWS.
• Utilize AWS services such as EKS, AWS Lambda, and AWS 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 AWS 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 AWS, 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 AWS 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 AWS 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 AWS.
• Expertise in AWS 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).

Why Join Us?

• Work on cutting-edge AI/ML projects in a dynamic multi-cloud environment.
• Opportunities for growth in AI/ML, cloud architecture, and MLOps.
• Competitive salary and benefits package.

Required Skills