RTL CAD Engineer

Job Summary

We are looking for an engineer to build AI-driven solutions that improve and automate RTL front-end design and implementation flows. The focus is on using agentic AI frameworks and modern open-source tooling to streamline common RTL-to-GDS workflow tasks and reduce manual effort.

Key Responsibilities

• Develop AI-based tools/agents to optimize RTL design and front-end flow execution, including automation around analysis, checks, and flow tasks.
• Build and maintain agentic workflows using modern open-source ecosystems (e.g., LangChain/CrewAI or similar frameworks).
• Create and improve automation and scripting that integrates with design tools and existing engineering workflows.
• Write, review, and maintain Python code with good engineering practices (readability, testability, maintainability).
• Quickly learn and adopt new AI packages and evolving best practices, as the ecosystem changes rapidly.

Required Qualifications

• Strong hands-on experience with Python scripting/automation (comfort writing + reviewing code).
• Basic understanding of VLSI RTL GDS flow and common front-end stages (RTL/design checks/synthesis/STA/CDC/formal/DV, etc.).
• Practical familiarity with agentic AI frameworks and tooling (LangChain, CrewAI, LangGraph, or similar open-source stacks).
• Ability to work independently, iterate quickly, and learn new tools/packages fast.

Nice to Have

• Hands-on experience applying LLM-driven techniques and solutions on large, production-quality SystemVerilog codebases
• Exposure to building multi-agent systems (supervisor/worker patterns, tool-calling, memory/context, RAG).
• Experience integrating automation with engineering infrastructure and reference flows

Minimum Qualifications

Bachelor''s degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 6+ years of Hardware Engineering or related work experience.

OR

Master''s degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 5+ years of Hardware Engineering or related work experience.

PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 4+ years of Hardware Engineering or related work experience.