About this role
Job Description and Requirements
We Are
Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.
You Are
You have spent 8+ years building and operating compute infrastructure that powers engineering teams doing work that cannot afford downtime or performance degradation. The systems you run are not back-office IT, they are the platform that determines whether a critical simulation finishes on time or a product milestone slips by three weeks. You understand that reliability at scale is a function of architecture, automation, and the decisions you make about job scheduling, storage, and cloud integration long before anyone notices a problem.
You are fluent in Linux, Python, and the operational realities of managing LSF, UGE, or Slurm across large HPC environments. You have debugged misconfigured queues, optimized cloud bursting strategies to balance cost and performance, and worked across IT, security, and R&D to align infrastructure roadmaps with business priorities. You do not need perfect requirements to move forward. You ask the right questions, synthesize conflicting stakeholder needs, and build solutions that work in production, not just in theory.
At Synopsys, you will manage the compute environments that enable the design of the chips powering AI, automotive, and next-generation systems. The infrastructure you build directly impacts product timelines and engineering productivity across the company.
What You'll Be Doing
- Enable engineering teams across Synopsys IPG to use on-premises and cloud compute environments for design, verification, and simulation workloads
- Translate requirements from business, engineering, cybersecurity, and data governance stakeholders into a technical roadmap and execute on it
- Manage and optimize job scheduler environments including LSF, UGE, or Slurm across large-scale HPC systems
- Support and troubleshoot Linux/UNIX systems in production, ensuring uptime and performance for engineering workflows
- Build and maintain DevOps automation using Python and other scripting languages to improve reliability and reduce manual toil
- Coordinate with IT, R&D, and infrastructure teams to align compute strategy, resolve issues, and deliver on engineering needs
- Manage cloud compute operations across GCP, AWS, or Azure, including cost optimization, security compliance, and hybrid cloud integration
The Impact You Will Have
- Engineering teams will have reliable, performant compute environments that let them focus on their work instead of fighting infrastructure
- The roadmap you build will shape how Synopsys scales compute capacity for next-generation IP and EDA development
- Your automation and scripting will reduce manual operations overhead and improve system reliability across the HPC environment
- R&D teams will be able to burst to cloud when needed without waiting weeks for approvals or configurations
- Your coordination across IT, security, and engineering will prevent bottlenecks and misaligned priorities before they slow down product timelines
- The job scheduler optimizations you implement will improve throughput and reduce queue wait times for critical engineering runs
- Your deep technical knowledge will make you the go-to resource when something breaks and needs to be fixed fast
What You'll Need
- Deep hands-on experience with Linux/UNIX system administration in production environments
- Proven experience managing and optimizing job schedulers such as LSF, UGE, or Slurm in large-scale HPC or engineering compute environments
- Strong scripting and automation skills, particularly in Python
- Experience supporting engineering teams using cloud platforms like GCP, AWS, or Azure
- Background in DevOps practices, tooling, and workflows
- Ability to translate technical, business, and security requirements into actionable roadmaps and coordinate across multiple stakeholder groups
- Experience managing HPC systems in large compute data centers is a strong plus
Who You Are
- You can sit in a meeting with IT, security, and R&D, hear three conflicting priorities, and walk out with a plan that actually works for all of them
- When something breaks in production, you do not panic or wait for someone else to fix it. You dig in, find the root cause, and get it back online
- You think in systems, not tickets. You see how a change in cloud policy affects job scheduling, which affects engineering timelines, which affects product launches
- You are comfortable saying no when a request does not make technical sense, and you can explain why in a way that does not shut down the conversation
- You do not need to be the smartest person in the room, but you do need to be the one who makes sure the infrastructure does not become the reason a team missed their milestone
The Team You'll Be Part Of
You will be part of the Synopsys IPG HPC team, which enables engineering teams across the IP Group to run their workloads on both on-premises and cloud compute infrastructure. This is a hands-on, technically deep team that works closely with R&D, IT, and security to keep compute environments running and evolving.
Rewards and Benefits
We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.
At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.