AWS Cloud Platform Engineer

System One Holdings, LLC

• $108K — $130K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years in cloud engineering, DevOps, or infrastructure engineering.
  • Hands-on experience with AWS services in a cloud-native environment.
  • Experience with AWS SageMaker or comparable enterprise ML/Data Science platform.
  • Proficient in scripting and automation using Python, shell, or similar.
  • Practical knowledge of Terraform and CI/CD pipelines.
  • Strong troubleshooting skills with a focus on root cause analysis.
  • Experience securing cloud environments, including IAM and access controls.

Responsibilities

  • Build automation and improve platform reliability and security.
  • Drive modernization efforts across the AWS ecosystem.
  • Deliver enhancements and resolve complex technical issues.
  • Strengthen engineering standards and support migration efforts.
  • Decommission legacy analytics systems as needed.

Benefits

  • Opportunity to work with cutting-edge analytics and machine learning technologies.
  • Collaborative work environment across various technology teams.
  • Professional growth in cloud engineering and automation practices.
  • Engagement in enterprise-scale ML infrastructure modernization.
Full 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.

Ref: #404-IT Pittsburgh

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