RTL Front-End Flow Optimization (CAD)

Overview

Engineer to build AI-driven solutions that improve and automate RTL front-end design and implementation flows, streamlining RTL-to-GDS workflow tasks and reducing manual effort.

What you'll do

• Develop AI-based tools/agents to optimize RTL design and front-end flow execution.
• Automate analysis, checks, and flow tasks.
• Build and maintain agentic workflows using open-source frameworks (e.g., LangChain/CrewAI).
• Create integration and automation scripts with design tools and existing engineering workflows.
• Write, review, and maintain Python code with good engineering practices.
• Quickly learn and adopt new AI packages and evolving best practices as tools change.

What you'll need

• Strong hands-on Python scripting/automation experience for writing and reviewing code.
• Basic understanding of the VLSI RTL-to-GDS flow and common front-end stages.
• Practical familiarity with agentic AI frameworks and tooling such as LangChain, CrewAI, or LangGraph.
• Ability to work independently and iterate quickly while learning new tools/packages.
• Bachelor’s degree plus 6+ years hardware engineering experience, or alternative degree/experience combinations (Master’s: 5+; PhD: 4+).

Nice to have

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

Details

• Location: Bangalore, India.