R&D Engineering, Principal Engineer

About the role

Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. The company delivers industry-leading silicon design, IP, simulation and analysis solutions, and design services, partnering closely with customers across a wide range of industries to maximize their R&D capability and productivity.

This role sits within 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. It is a hands-on, technically deep team that works closely with R&D, IT, and security to keep compute environments running and evolving.

The ideal candidate has 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. They understand 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 weeks earlier, and they see that coming and fix it before anyone files a ticket. They are comfortable moving between on-premises data centers and cloud environments without losing sight of what matters: uptime, performance, and cost. They speak Linux and Python fluently, have managed LSF, UGE, or Slurm in production, and know what breaks when a queue gets misconfigured or a node goes rogue. They do not need a perfect requirements doc to get started; they talk to the R&D team, the IT team, the security team, and figure out what the actual problem is and what the roadmap should look like.

The compute environments managed in this role are not back-office infrastructure — they are the platform that makes the work possible for engineering teams building the tools that design the chips that power everything.

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

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

Qualifications

• 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, does not panic or wait for someone else to fix it — digs in, finds the root cause, and gets it back online
• Thinks in systems, not tickets; sees how a change in cloud policy affects job scheduling, which affects engineering timelines, which affects product launches
• Comfortable saying no when a request does not make technical sense, and can explain why in a way that does not shut down the conversation
• Does not need to be the smartest person in the room, but ensures the infrastructure does not become the reason a team missed their milestone