Description
Synopsys software engineers are key enablers in the world of Electronic Design Automation (EDA), developing and maintaining software used in chip design, verification and manufacturing.
You have spent 8+ years building and operating compute infrastructure that powers engineering teams doing work that cannot afford downtime or performance degradation. 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.
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.
Responsibilities
- 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
Requirements
- 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
Benefits
- Comprehensive medical and healthcare plans that work for you and your family
- Time away: company holidays, ETO and FTO Programs
- Family support: maternity and paternity leave, parenting resources, adoption and surrogacy assistance, and more
- ESPP: purchase Synopsys common stock at a 15% discount, with a 24-month look-back
- Retirement plans: save for your future with our retirement plans that vary by region and country
- Competitive salaries