Date posted 05/31/2026
This position is open to hiring in Mississauga (Preferred) as well as Ottawa.
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 years building infrastructure that does not just run simulations, it powers the decisions engineers make when those simulations finish. You understand that compute and storage are not just resources to manage, they are the foundation that determines whether a team can iterate fast or gets stuck waiting. You have learned that the hardest part of scaling infrastructure is not adding more machines, it is designing systems that stay reliable, predictable, and usable as complexity grows.
You think in layers. You know that AI tools are only as smart as the data they can access, and you have seen firsthand what happens when that data is stale, unstructured, or siloed. Building a knowledge platform is not just database work to you, it is architecture that connects specs to code to tests so AI can reason across domains, not just retrieve flat records. You do not wait for perfect requirements. You ask the right questions, prototype quickly, and build systems that can absorb change without breaking. When something goes wrong, you are the person who digs into logs, traces the failure back to root cause, and fixes it in a way that prevents the next three incidents. At Synopsys, you will work on infrastructure and knowledge systems that directly enable semiconductor design teams to move faster and smarter.
What You'll Be Doing
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Manage and optimize compute and disk resources across HPC environments to support large-scale simulation workloads, ensuring high availability and performance for critical design tasks
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Monitor, troubleshoot, and scale compute infrastructure in collaboration with IT and infrastructure teams, diagnosing bottlenecks and resolving issues before they impact engineering timelines
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Develop and implement resource utilization strategies including job scheduling with LSF, load balancing, and storage optimization to maximize throughput and minimize idle time
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Build custom automation scripts and tools in Python, Tcl, or similar languages to eliminate repetitive manual tasks and integrate seamlessly into existing simulation workflows
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Architect and maintain a structured, AI-ready knowledge database that serves as the single source of truth, connecting specifications, code, tests, and design artifacts so AI tools can reason across domains, not just search flat tables
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Establish build, validation, and release processes for the knowledge platform with automated checks, versioned builds, staging environments, and rollback plans so teams and AI tools always work against verified, release-ready data
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Design scalable, multi-project infrastructure where core schema, tooling, and validation frameworks are
