Senior Principal Software Engineer - Compute System & EDA Infrastructure

ards 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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