Agentic AI engineer

AI Coding Agent Applications
•Proficiently utilize AI Coding Assistants such as Claude Code, GitHub Copilot, and Cursor to accelerate development workflows
•Design and craft effective Prompts to guide LLMs in generating high-quality EDA scripts (TCL / Python)
•Leverage AI Agents to automate the generation, review, and refactoring of Flow scripts to improve development efficiency
•Explore the potential of LLM-based EDA Flow Co-pilots to assist engineers in making flow-related decisions
•Evaluate and integrate AI Coding tools into the department's development lifecycle (AI-assisted SDLC)
Research and Innovation
•Track the latest academic research and industry trends in AI for EDA, ML for CAD, and LLM for CAD
•Collaborate with EDA Vendors (Synopsys / Cadence / … ) to explore AI integration opportunities
•Investigate the application of Agentic AI Workflows for multi-step EDA Flow automation

Requirements

1.Required Qualifications
•Programming Languages:Python, TCL, Shell Script
•ML Frameworks:PyTorch / TensorFlow / Scikit-learn
•Data Processing:Pandas, NumPy, SQL
•AI Coding Tools:Hands-on experience with Claude Code / Cursor / GitHub Copilot
•Prompt Engineering:Ability to design effective Prompts to generate functional engineering scripts and code
•Education:Master's degree or above in Electrical Engineering, Computer Science, or related fields
2.Preferred Qualifications
•Experience developing internal tools using LLM APIs (Claude / GPT / Gemini)
•Familiarity with RAG (Retrieval-Augmented Generation) architecture, with the ability to build EDA knowledge base Q&A systems
•Experience in Multi-agent system design, capable of coordinating multiple AI Agents to collaboratively complete complex EDA tasks
•Understanding of physical design concepts such as Timing Analysis, DRC, IR-drop, and Signal Integrity
•Familiarity with APR stages including Floorplan, CTS, and Routing
•Prior experience in EDA Flow development or Tape-out is a strong plus
Education: Master's Degree