AWS Cloud Platform Engineer

System One; Lafayette (LA); On-site; USD 140,000 - 180,000; Full time

Job summary

System One is seeking a Senior Cloud Platform Engineer to reinforce enterprise Analytics, Data Science, and ML platforms. The role focuses on AWS SageMaker and related tooling, delivering hands-on engineering support and platform improvements.

The engineer will build automation, harden security, and modernize enterprise-scale ML infrastructure while collaborating with cross-functional teams across security, DevOps and data platforms.

Qualifications

• 8+ years in cloud engineering or DevOps.
• Hands-on AWS and SageMaker experience.
• Scripting with Python, shell, or similar.
• Terraform and CI/CD experience.
• Security, access controls, and remediation practices.

Responsibilities

• Build automation and improve platform reliability and security.
• Drive modernization across the AWS ecosystem.
• Collaborate with security, DevOps, and app teams and vendors.
• Support migration and decommissioning of legacy analytics systems.

Skills

AWS

SageMaker

Python

Terraform

CI/CD

Security

Monitoring

FinOps

Automation

Documentation

Education

Bachelor's degree in Computer Science / Information Systems

Job description

Job Title: Senior Cloud Platform Engineer

Duration: Full Time / Permanent Position

Location: Lafayette, LA, Knoxville, TN, Birmingham, AL

Work Mode: Onsite 5 Days

Position Description

Systemone is seeking an experienced Senior Cloud Platform Engineer to strengthen its enterprise Analytics, Data Science, and Machine Learning platforms. This role provides hands on engineering support across AWS based analytics environments, with a strong focus on AWS SageMaker and related Data Science tooling.

Your Future Duties and Responsibilities

The engineer will build automation, improve platform reliability and security, and drive modernization efforts across the AWS ecosystem. Working closely with platform engineers and cross functional technology partners, this person will deliver enhancements, resolve complex technical issues, strengthen engineering standards, and support ongoing migration and decommissioning efforts tied to legacy analytics systems. This is a great opportunity for a hands on cloud engineer who enjoys automating repetitive work, tightening up security posture, and modernizing enterprise scale ML infrastructure.

Required Qualifications to Be Successful in This Role

• 8+ years in cloud engineering, DevOps, or infrastructure engineering.
• Solid hands on experience with AWS services in a cloud native environment.
• Experience working with AWS SageMaker or a comparable enterprise ML/Data Science platform.
• Comfortable scripting and automating with Python, shell, or similar.
• Practical experience with Terraform and CI/CD pipelines.
• Strong troubleshooting chops — root cause analysis and building fixes that actually stick.
• Background securing cloud environments (IAM, access controls, vulnerability remediation).
• Experience with monitoring/observability tools and performance tuning.
• Some exposure to cloud cost optimization or FinOps practices.
• Can build automation that cuts down manual, repetitive operational work.
• Comfortable writing clear documentation and collaborating across teams (security, DevOps, app teams, vendors).

Desired Skillset

• Domino Data Lab or similar enterprise ML platform experience.
• Python based Data Science/ML workload experience.
• GitLab pipeline experience.
• Experience with AWS cost management/FinOps.
• Background in platform migrations or system decommissioning.
• SAS experience (helpful for legacy system closeout, not required).

Educational Requirements

Bachelor's degree in Computer Science, Information Systems, or a related field.