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# Principal Systems Engineer - Cloud Services

- **Company:** Stanford Health Care
- **Location:** Palo Alto, CA, United States
- **Experience:** Expert
- **Salary:** $164,757.0 - $218,338.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Systems Engineering, Microsoft Azure, Software as a Service, Cloud Computing, Cloud Computing Security, Cloud Engineering, Information Systems, Information Engineering, DevOps, Domain Name System (DNS), Github, Infrastructure as a Service (IaaS), Identity and Access Management, Machine Learning, Platform as a Service (PAAS), Cloud Services, Google Cloud, Load Balancing, Generative AI, Firewalls (Computer Science), Containerization, Kubernetes, Information Technology, Machine Learning Operations, Cloud Optimization, Terraform, Data Pipelines, Docker, Databricks
- **Published:** October 26, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3467212553&tx=JL7973FFJ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* BS DEGREE IN INFORMATION TECHNOLOGY, INFORMATION SYSTEMS, BUSINESS MANAGEMENT, BUSINESS ANALYTICS, BUSINESS ADMINISTRATION OR A DIRECTLY RELATED FIELD FROM AN ACCREDITED COLLEGE OR UNIVERSITY.

Experience Qualifications

 * Seven (7) years of progressively responsible and directly related work experience required.
 * Ten (10) years of progressively responsible and directly related work experience preferred.

Required Knowledge, Skills and Abilities

 * Cloud Platforms: Proficiency in major cloud platforms such as AWS, Azure, and Google Cloud.
 * Cloud Services: Understanding various cloud services, including IaaS, PaaS, and SaaS.
 * Modern Applications: Support the deployment and lifecycle management of generative AI models and ML workflows.
 * Security: Thorough understanding of cloud security architecture, data protection, identity management, and compliance requirements.
 * Networking: In-depth understanding of cloud networking architecture, such as virtual networks, firewall load balancing, and DNS.
 * Automation: Deep understanding of automation technologies, including containerization (Docker, Kubernetes) and DevOps practices.
 * Technical Expertise: Strong technical skills in cloud infrastructure management, including deployment, configuration and maintenance.
 * Monitoring and Optimization: Ability to monitor cloud services and optimize performance and cost.
 * Troubleshooting: Proficiency in diagnosing and resolving cloud-related issues.
 * Security Implementation: Skills in implementing and managing security measures such as firewalls, encryption, and access controls.
 * Documentation: Ability to maintain comprehensive documentation of cloud configurations, procedures, and policies.
 * Problem-Solving: Excellent problem-solving skills to address complex cloud infrastructure challenges.
 * Communication: Strong communication skills to collaborate effectively with cross-functional teams and provide technical support.
 * Adaptability: Ability to adapt to new technologies and continuously learn about advancements in cloud computing.
 * Project Management: Capable of managing cloud projects, including planning, execution, and monitoring.
 * Security Awareness: Keen awareness of best practices and the ability to implement them in cloud environments.

Physical Demands and Work Conditions

Blood Borne Pathogens

 * Category III - Tasks that involve NO exposure to blood, body fluids or tissues, and Category I tasks that are not a condition of employment

## Description

As a Principal System Engineer - Cloud Services, You will oversee Stanford Health Care's cloud infrastructure, managing deployment, optimization, and support of cloud-native applications and services to ensure high performance and security. This role is vital for supporting initiatives related to modern application platforms, generative AI, machine learning, data engineering pipelines, Databricks environments, and DevOps frameworks. You will work closely with different departments to support their cloud-based applications and services, troubleshoot issues, and implement solutions

to enhance the overall cloud environment., * Cloud Infrastructure Management: Design, implement, and manage scalable cloud infrastructure (Azure/AWS/GCP) to support modern applications and AI/ML workloads

 * Solution Architecture:. Create business cases for new technology solutions, including Generative AI initiatives. Collaborate with data engineering teams to improve data pipelines and maintain Databricks environments. Confidently present and defend solutions, approaches, timelines, and critical aspects.
 * Technical Expertise: Enable and maintain CI/CD pipelines and infrastructure-as-code (IaC) practices using tools like Terraform, GitHub Actions, or Azure DevOps.
 * Support and Troubleshooting: Provide technical support to internal teams and resolve cloud-related issues promptly. Perform root cause analysis and implement preventive measures.
 * Monitoring and Optimization: Monitor cloud services to ensure they run efficiently and securely. Implement performance tuning and optimization strategies as needed.
 * Security and Compliance: Ensure that cloud environments adhere to security policies and compliance standards. Implement and manage security measures such as firewalls, encryption, and access controls.
 * Automation and Scripting: Develop and maintain automation scripts to streamline cloud operations and reduce manual intervention.
 * Documentation and Reporting: Acts independently in leading projects and engaging senior management, including Service Line Leaders,
 * Department Chairs, and executives. Maintains documentation of cloud configurations, procedures, and policies. Generates reports on cloud usage, performance, and security.