Remote AI Cloud Solutions Architect

Akkodis; Chicago (IL); Remote; USD 117,000 - 124,000; Full time

Job summary

Akkodis seeks a Solution Architect for a contract role with a client in Chicago, IL—remote. The ideal candidate will bring strong hands-on experience with AI services (Bedrock, SageMaker), CI/CD, Terraform, and GCP, plus deep AWS expertise across S3, EC2, RDS, Lambda, and security.

Expect a rate Range: $85/hr–$90/hr, negotiable based on experience. The role requires 6+ years in engineering, 4+ years in AWS data engineering/arch, and a proven track record in designing scalable data pipelines and

Qualifications

• 6+ years in application/platform engineering or related work.
• 4+ years in AWS cloud data engineering/architecture and best practices.
• Experience with data warehousing platforms like Snowflake/Redshift.
• Strong AWS services knowledge: S3, EC2, RDS, Lambda, CloudFormation, Kinesis, EMR, Step Functions, VPC, IAM, Security Groups.
• Proficient in SQL, Python, PostgreSQL, AWS Aurora/RDS, MongoDB, Redis.
• CI/CD tooling and scripting (GitHub Actions, Jenkins, AWS CodePipeline, Terraform).
• Strong IAM and cloud security understanding.
• Skilled in monitoring/alerts for cloud resources and cloud security.

Skills

CI/CD

Python scripting

PowerShell scripting

enterprise architecture

Communication

Education

BA/BS in Computer Engineering or Computer Science

Tools

AWS

S3

EC2

RDS

Lambda

CloudFormation

Kinesis

Terraform

GCP

Bedrock

SageMaker

Kubernetes

Docker

Fargate

Snowflake

Redshift

GitHub Actions

Jenkins

Job description

Akkodis seeks a Solution Architect for a contract role with a client in Chicago, IL—remote. The ideal candidate will bring strong hands-on experience with AI services (Bedrock, SageMaker), CI/CD, Terraform, and GCP, plus deep AWS expertise across S3, EC2, RDS, Lambda, and security.

Expect a rate Range: $85/hr–$90/hr, negotiable based on experience. The role requires 6+ years in engineering, 4+ years in AWS data engineering/arch, and a proven track record in designing scalable data pipelines and