Remote AWS Solutions Architect – AI/ML Cloud Modernization

Cloudelligent; Richmond (VA); Remote; USD 150,000 - 230,000; Full time

Job summary

Cloudelligent is seeking an AWS Solutions Architect- AI/ML to design scalable cloud architectures and lead modernization initiatives for clients. You will focus on AWS-native data pipelines, AI/ML integration, and multi-region deployments, guiding teams from pre-sales through delivery to achieve business outcomes.

You will collaborate with clients, data engineers, and cross-functional teams, applying Well-Architected principles, security best practices, and advanced Generative AI use cases to

Qualifications

• 8+ years of experience designing, building, and operating solutions on AWS.
• Strong knowledge of AWS Well-Architected patterns and workloads for modernization, data, and AI/ML.
• Experience migrating legacy apps to AWS with containers and serverless.
• Proficiency with Terraform or CloudFormation for IaC.
• Experience in pre-sales and client-facing roles.

Responsibilities

• Architect cloud-native solutions and lead app modernization on AWS.
• Design data pipelines and AI/ML integrations to enhance operations.
• Lead pre-sales discussions and align client needs with solutions.
• Define cloud governance and security practices for compliance.
• Lead migrations and multi-region deployments with cloud-native architecture.
• Stay current with cloud tech, Generative AI, and data engineering.

Skills

AWS

Data pipelines

SageMaker

Bedrock

Redshift

Terraform/CloudFormation

Docker/ECS/EKS

Serverless

Security & Compliance

Pre-sales

Job description

Cloudelligent is seeking an AWS Solutions Architect- AI/ML to design scalable cloud architectures and lead modernization initiatives for clients. You will focus on AWS-native data pipelines, AI/ML integration, and multi-region deployments, guiding teams from pre-sales through delivery to achieve business outcomes.

You will collaborate with clients, data engineers, and cross-functional teams, applying Well-Architected principles, security best practices, and advanced Generative AI use cases to