Provide central engineering support for EDA tools, software platforms, and design workflows, including analog/mixed‑signal flows, physical verification, design data management, and compute infrastructure
Develop, enhance, and maintain automation scripts and software tools (primarily in Python, with Tcl/Bash/Perl/SKILL as needed) to support environment setup, diagnostics, workflow validation, and operational tasks
Implement software solutions for log analysis, issue triage, regression checks, and monitoring of EDA and infrastructure workflows
Apply AI‑assisted techniques to improve support efficiency, including use of LLMs for diagnostics support, documentation generation, and guided troubleshooting, with exposure to EDA AI concepts such as agent‑based workflow optimization
Investigate and resolve tool, access, permission, configuration, and environment issues, providing clear root‑cause analysis and documented resolutions
Reproduce reported issues by creating test cases and validation scenarios, submit internal and vendor bug reports, and track issues to closure
Troubleshoot performance and reliability issues in collaboration with IT and EE development teams, including interaction with job schedulers and resource management systems
Support EDA and software licensing operations, including availability, usage, and integration with automated workflows
Contribute to cloud‑based automation efforts, including interaction with AWS‑hosted services or compute environments where applicable
Create and maintain knowledge base content, FAQs, and internal documentation, with a focus on enabling self‑service and reducing recurring support issues
Requirements
Bachelor’s degree (Master’s preferred) in Computer Science, Electronics Engineering, or a related field
3–5 years of relevant experience in EDA, CAD, software, or engineering enablement roles
Proven experience with automation and software development, using one or more of: Python, Tcl, Bash, Perl, SKILL
Familiarity with revision control systems, issue tracking, and collaboration tools
Strong communication and interpersonal skills, with the ability to explain complex technical topics clearly
Detail‑oriented, well‑organized, and effective in a collaborative engineering environment
Experience with Git, Perforce, or SVN (preferred)
Familiarity with the Cadence and/or Synopsys design platform (preferred)
Familiarity with Siemens‑Mentor Calibre tools and physical verification flows (preferred)
Exposure to deep‑submicron semiconductor manufacturing technologies (preferred)
Hands‑on or applied exposure to: LLMs and AI‑assisted automation EDA AI techniques, including intelligent agents and optimization‑driven flows (preferred)