Senior Principal Software Engineer – Compute System & EDA Infrastructure
Role summary
Cadence is seeking a Senior Principal Software Engineer to join their Compute System & EDA Infrastructure team. This role involves architecting, designing, and developing core components of a large-scale compute system, including distributed job scheduling, high-throughput data services, and monitoring tools. The engineer will work on integrating compute infrastructure with advanced EDA workflows, analyzing and resolving complex distributed systems issues, and improving system performance, scalability, and reliability. The position requires strong C/C++ proficiency, experience with backend systems or distributed compute frameworks, and a solid understanding of algorithms and system design. Preferred qualifications include 5+ years of experience and familiarity with languages like Python, Go, TypeScript, or Rust.
## At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.
Senior Principal Software Engineer – Compute System & EDA Infrastructure
About the Role
This is an exceptional opportunity to join a global leader in computational software, pioneering AI‑driven and digital‑twin‑enabled design technologies that accelerate innovation across industries. According to Cadence’s latest corporate overview, the company is a market leader in AI and Intelligent System Design, providing essential computational platforms used by the world’s top semiconductor and systems companies to build next‑generation products—from silicon to full electromechanical systems.
Our team develops the compute system that powers large‑scale EDA workflows. This includes a distributed scheduler, high‑throughput data services, and dashboards enabling visibility and orchestration across complex engineering workloads. You will work at the intersection of large compute infrastructures, advanced EDA algorithms, and cross‑team system integration.
Responsibilities
- Architect, design, and develop core components of the compute system, including:
- Distributed job scheduling and workload orchestration
- High‑performance data services and metadata management
- Dashboard, monitoring, and system observability tools
- Build robust integrations between compute infrastructure and advanced EDA workflows.
- Lead end‑to‑end design discussions and drive technical direction for multi‑team, multi‑component systems.
- Analyze, debug, and resolve highly complex issues across distributed systems, data pipelines, and workflow coordination.
- Implement new features that improve performance, scalability, and reliability of large‑scale analysis workloads.
- Mentor engineers, drive engineering best practices, and influence architectural decisions across organizational boundaries.
- Collaborate closely with cross‑functional teams including product engineering, runtime infrastructure, DevOps, and customer engineering.
- Troubleshoot customer scenarios, perform root‑cause analysis across logs/telemetry, and provide high‑quality solutions.
Minimum Qualifications
- MS/BS in Computer Science, Electrical Engineering, Computer Engineering, or related field.
- Strong understanding of algorithms, data structures, and system-level software design.
- Proficiency in C or C++, including debugging, optimization, and large‑codebase development.
- Experience building backend systems or distributed compute frameworks.
Preferred Qualifications
- 5+ years of professional software engineering experience, ideally in system‑level or distributed system development.
- Proficiency with one or more additional languages:
- Python
- Go
- TypeScript
- Rust
- Experience with Angular or other modern frontend frameworks.
- Familiarity with large‑scale compute workflows, job scheduling, cluster systems, or HPC environments.
- Strong troubleshooting skills, particularly in distributed, performance‑sensitive, or multi‑component systems.
- Excellent cross‑team communication and the ability to lead initiatives across multiple engineering groups.
- Ability to work in fast‑paced environments and quickly learn new technologies.
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