Job description

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 10+ years keeping compute infrastructure running for engineers who need it to just work, not sort of work, actually work when they are pushing a deadline or running a critical simulation at 2 a.m. You know that the difference between a good HPC environment and one that slows down a product launch is usually a decision about job scheduling, storage latency, or cloud bursting made six weeks earlier, and you are the kind of engineer who sees that coming and fixes it before anyone files a ticket. You are comfortable moving between on-premises data centers and cloud environments without losing sight of what matters: uptime, performance, and cost. You speak Linux and Python fluently. You have managed LSF, UGE, or Slurm in production, and you know what breaks when a queue gets misconfigured or a node goes rogue. You do not need a perfect requirements doc to get started. You talk to the R&D team, the IT team, the security team, and you figure out what the actual problem is and what the roadmap should look like. At Synopsys, you will work with engineering teams building the tools that design the chips that power everything. The compute environments you manage are not back-office infrastructure. They are the platform that makes the work possible. 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. In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.

Requirements

Must-haves

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

Nice-to-haves

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Platform: avature
Effort: medium

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