> Markdown version of [/jobs/ext/3863615-lead-eda-software-engineer](https://www.wearedevelopers.com/jobs/ext/3863615-lead-eda-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead EDA Software Engineer - **Company:** Cadence Design Systems, Inc. - **Location:** San Jose, United States - **Experience:** Expert - **Salary:** $119,000.0 - $221,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Unix, C++ (Programming Language), Cloud Computing, Computer Engineering, Data Structures, Database Design, Linux, Distributed Systems, Electronic Design Automation, Machine Learning, Software Engineering, Distributed Programming, Information Technology - **Published:** October 22, 2026 - **Apply:** https://startup.jobs/lead-eda-software-engineer-c-characterization-secure-ic-france-10541527 ## About the Role * 5+ years of experience in development of EDA tools and expertise in one or more areas: transistor-level timing, power, noise, aging, reliability, and EMIR analysis. * Hardcore C++ knowledge, particularly in a Linux environment. * Strong proficiency in designing data structures, algorithms, and applying software engineering principles. * Industry experience developing and maintaining C++ based applications on Unix or Linux platforms. Requirements * Experience with quality and software processes. * Proficiency in designing data structures, algorithms, and software engineering principles. * Ability to analyze transistor or gate-level schematics. * BS degree in Computer Science, Electrical Engineering, or Computer Engineering preferred. Nice-to-Have Skills * Experience in development of circuit simulation or library characterization programs. * Understanding of SPICE simulation transistor models at a high level. * Experience with distributed programming, database design, and cloud APIs for distributed computing. ## Description * Enhance and expand existing tools' architecture to cover timing analysis. * Create new frameworks for analyzing effects dominant at n5 and below. * Leverage machine learning technology to achieve significant improvements in speed, capacity, and usability over existing solutions.