Job Title: AWS Platform Architect / Engineer (Gen AI & AI/ML Integration)
Location: Atlanta, GA (Onsite)
Contract
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 server less 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 Sage Maker 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, Sage Maker 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, Data dog, 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, Sage Maker, 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.
· Bachelors or Master’s degree in Computer Science, Data Science, or a related field (or equivalent experience).
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