Cloud Platform Engineer

Position Summary

The Cloud Platform Engineer will design, build, configure, and support enterprise infrastructure platforms across Linux, Unix, Windows, and cloud-based operating environments. This role supports workloads across AWS, Microsoft Azure, and private cloud platforms such as Azure Local, with a focus on reliability, security, automation, and operational scalability.

The role combines systems administration, cloud engineering, infrastructure automation, and DevOps practices to provision, configure, patch, monitor, and maintain scalable compute, storage, network, and platform services. The engineer will use tools such as Azure DevOps, CI/CD pipelines, scripts, and infrastructure-as-code(Terraform) patterns to standardize deployments and improve operational consistency.

The ideal candidate has hands-on experience with Linux and Windows administration, virtualization, containers, cloud-native services, monitoring tools, security patching, and performance optimization.

This role may also support physical server builds, hardware lifecycle activities, IBM logical partition environments, and related enterprise platform operations as business needs require.

This position also supports infrastructure used for machine learning and advanced analytics workloads, including environments for model training, testing, deployment, monitoring, and lifecycle automation.

This position is hybrid, working from your remote office and Oakland, CA once per week, or more, based on business needs or company requirements.

Compensation

PG&E is providing the full salary/pay range for this position. The actual amount paid to an individual will be based on multiple factors, including, but not limited to, internal equity,specific skills, education, licenses or certifications, experience, market value, and geographic location. The range to reasonably expect will be between the minimum and midpoint listed below. The final decision will be made on a case-by-case basis related to the factors above. This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.

Bay Area Min: $102,000.00

Bay Area Mid: $132,000.00

Bay Area Max: $162,000.00

Job Responsibilities

• Design, build, test, and deploy cloud-based infrastructure services across compute, storage, network, and operating system layers.

• Assist with infrastructure asset deployment, utilization, acquisition, lifecycle status, and disposition activities to identify platform risks and capacity needs.

• Deploy operating system updates, security patches, configuration changes, and infrastructure reports across environments.

• Troubleshoot and resolve issues across operating systems, virtual machines, cloud services, storage platforms, backup services, monitoring agents, and infrastructure components.

• Collect, review, and analyze logs, alerts, utilization trends, and performance metrics.

• Assist in technical solution options that address reliability, scalability, security, automation, performance, and cost optimization requirements.

• Build, configure, patch, and support virtual machines in virtualized environments.

• Build, configure, and support IBM logical partitions, including coordination with compute, storage, network, and operating system teams.

Qualifications

Minimum:

• Bachelor's degree in computer science, job-related discipline, or equivalent experience.

• 2 years of hands-on experience in infrastructure, systems administration, cloud operations, or related Information Technology functions.

• 1 year of experience supporting cloud technologies, cloud services, infrastructure automation, or cloud-based operating environments.

• Experience working in an Agile/Scrum environment.

• AWS Certified CloudOps Engineer or Certified Azure Administrator or equivalent Cloud Platform certification.

Desired:

• Knowledge of AWS and Azure cloud services, including compute, storage, networking, IAM, EC2, Lambda, containers, and automation services.

• Understanding Agile/Scrum principles and team-based delivery practices.

• Familiarity with CI/CD practices, Azure DevOps, release pipelines, source control, automated testing, and deployment automation.

• Knowledge of systems administration across Linux, Unix, Windows Server, and AIX operating system platforms.

• Understanding of AI and machine learning development lifecycle concepts, including model build, validation, deployment, monitoring, and retraining workflows.

• Knowledge of machine learning platforms, data pipelines, model hosting environments, containerized workloads, and operational support processes.

• Ability to deliver work in sprints and collaborate effectively with cross-functional teams.

• Experience with scripting or application development using tools or languages such as PowerShell, Bash, Python, YAML, or similar automation technologies is a plus.

• Experience managing performance scorecards, dashboards, or benchmarking processes is a plus.