Staff Systems Engineer (Cloud Operations & Support)

Location: San Jose, CA OR Austin, TX, or Remote US

We are seeking a highly skilled and experienced Cloud Operations and Support Engineer to join our team. This is a hands-on, senior individual contributor role that will be pivotal in operations, and support of our cloud infrastructure. You will be responsible for the entire lifecycle of our cloud environment, from architecting and building high-performance clusters with CPUs and GPUs to deploying and optimizing our multi tenant cloud services in both private and public cloud infrastructure.

Responsibilities

• Supporting multiple geological locations to serve user communities across North America, Europe, and Asia sites.

• Focusing on improving customer productivity and committing to customer success. 

• Driving the overall operational strategy for internal High-Performance Compute (HPC) clusters in Cadence cloud.

• Maintaining, enhancing, monitoring, reporting, and improving its efficiency.

Requirements

• 8+ years of technical experience architecting, managing, and improving a HPC environment running Linux.

• At least 3 years working in a global group, coordinating support, strategies, projects, and operations across multiple geographies in a team-oriented approach

• Solid understanding and proven operational experience with HPC clusters, job submission/management technologies, cloud, and associated management tools.

• Proven experience working directly with engineering teams to collaboratively develop solutions to optimize their working environment (Direct EDA experience desired)

• Proven experience in capacity and performance management, optimizing performance, ensuring adequate capacity, working with customers on optimization of their workloads, and development and maintenance of key performance indicators

• A proven process focus shown through documentation, change management, incident management and problem-resolution activities

• Extensive hands-on experience with Docker: image management, container orchestration, and troubleshooting.

• Deep expertise in Linux system administration (RHEL preferred), including networking, storage, and performance tuning. 

• Familiarity with user authentication and integration using systems like LDAP or Active Directory.

• Solid understanding and proven operational experience with HPC clusters, job submission/management technologies, cloud, and associated management tools.

• Hands-on GPU Cluster Management: Experience in configuration, installation, and optimization of GPU server clusters. This includes advanced troubleshooting of hardware and software, performance tuning, and implementing best practices for cluster utilization and resource management. Hands-on technical experience managing GPU VMS, installing, configuring instances and other services over OpenStack

• Automation & Monitoring: Develop and maintain automation scripts using languages like Python, Bash, or Perl to streamline system maintenance, deployment, and reporting. Implement and manage monitoring solutions for system health, job statuses, GPU utilization, and container performance to proactively identify and resolve issues.

• Strong problem-solving and communication skills with the ability to work in a multi platform, cross-functional, and geographically distributed team. Proven experience working directly with internal or external Customers to collaboratively develop solutions to optimize their working environment (Direct EDA experience desired)

Education: BS / MS in computer science or related field

The hourly range for California is $57.21 to $106.25 per hour. You may also be eligible to receive incentive compensation: bonus, equity, and benefits. Please note that the hourly range is a guideline and compensation may vary based on factors such as qualifications, skill level, competencies and work location. Our benefits programs include: paid vacation and paid holidays, 401(k) plan with employer match, employee stock purchase plan, a variety of medical, dental and vision plan options, and more.