RTL Front-End Flow Optimization (CAD)

Location: Bangalore, India

Department: Hardware Engineering

Work Location: onsite

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Hardware Engineering

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

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