AI Engineer - RTL Front-End Flow Optimization

Job description

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