Staff / Senior Staff CAD & Methodology Engineer (Digital Implementation & Signoff)

The role

You will architect, develop, and maintain automated physical design and signoff flows from synthesis through GDSII. You will optimize Cadence Innovus and Tempus methodologies to achieve PPA targets for AI accelerator architectures.

What you will do

• Architect, develop, and maintain a highly automated physical design and signoff flow.
• Drive advanced physical design methodologies in Cadence Innovus.
• Optimize recipes for floorplanning, placement, CTS, routing, and power grid implementation.
• Own the STA and timing signoff methodology using Cadence Tempus.
• Implement and optimize DMSA, advanced OCV methodologies, and automated Tempus ECO flows.
• Develop Python and Tcl-based automation and custom utilities to reduce turnaround time.
• Act as the primary technical liaison with Cadence.
• Drive tool evaluations and beta testing of new features.
• Serve as the final escalation point for PD and Timing teams.
• Document methodologies and mentor junior engineers.

Required qualifications

• 9 to 14 years of industry experience in ASIC/SOC physical design, with a focus on CAD, TFM, or flow automation.
• Deep, production-proven expertise with Cadence Innovus and Cadence Tempus.
• Strong understanding of internal tool mechanics, database access commands (dbGet), and advanced tool configuration.
• Expert-level proficiency in Tcl and Python.
• Strong background in Makefile generation, shell scripting, and version control (Git/Perforce).
• Thorough understanding of deep sub-micron physical design concepts (advanced node DRCs, cross-talk, electromigration, IR drop).
• Thorough understanding of the theoretical foundations of Static Timing Analysis.
• Ability to thrive in a fast-paced, dynamic environment.
• Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, Computer Engineering, or a related discipline.

About the company

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. Launched in 2022, the company builds next-generation accelerators with massive compute density using in-memory computing technology.