Top Tech TransitionBrowse all jobs
En Charge AI

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

Apply on En Charge AI

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

We are an ambitious AI hardware startup building next-generation accelerators with massive compute density. To achieve aggressive Power, Performance, and Area (PPA) targets on accelerated tapeout schedules, we require a robust, highly automated, and heavily optimized physical implementation and signoff flow.

The Role

As a Staff / Senior Staff CAD & Methodology Engineer, you will be the resident expert in Innovus and Tempus, responsible for developing, debugging, and continually accelerating our RTL-to-GDSII and timing signoff flows. You will work closely with Physical Design and STA leads to eliminate bottlenecks, automate manual tasks, and push the limits of EDA capabilities at advanced process nodes.

Key Responsibilities

Requirements & Qualifications

•

Experience: 9 to 14 years of industry experience in ASIC/SOC physical design, with a primary focus on CAD, TFM (Tools, Flows, and Methodology), or flow automation.

•

Cadence Mastery:

•

•

•

Scripting & Software Skills: Expert-level proficiency in Tcl and Python. Strong background in Makefile generation, shell scripting, and version control (Git/Perforce).

•

Domain Knowledge: Thorough understanding of deep sub-micron physical design concepts (advanced node DRCs, cross-talk, electromigration, IR drop) and the theoretical foundations of Static Timing Analysis.

•

Startup Mindset: Ability to thrive in a fast-paced, dynamic environment where flow requirements evolve rapidly as the architecture matures.

•

Education: Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, Computer Engineering, or a related discipline.

You apply directly on En Charge AI's careers site. See similar jobs