AWS Cloud Platform Engineer

Full Time / Permanent Position | Location: Lafayette, LA, Knoxville, TN, Birmingham, AL | Work Mode: Onsite 5 Days

About the role

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.

Responsibilities

• Build automation, improve platform reliability and security, and drive modernization efforts across the AWS ecosystem.
• Work closely with platform engineers and cross‑functional technology partners to deliver enhancements, resolve complex technical issues, strengthen engineering standards, and support ongoing migration and decommissioning efforts tied to legacy analytics systems.
• Enjoy automating repetitive work, tightening up security posture, and modernizing enterprise‑scale ML infrastructure.

Qualifications

• 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 skills — 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.
• Ability to build automation that cuts down manual, repetitive operational work.
• Comfortable writing clear documentation and collaborating across teams (security, DevOps, app teams, vendors).
• Bachelor’s degree in Computer Science, Information Systems, or a related field.

Skills

• 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).