Lead Engineer - AI

AMD AMD · Semiconductors · Bangalore, India · Engineering

Lead Engineer for AI at AMD, focusing on developing and deploying AI-powered tools and platforms to enhance RTL design and verification productivity within the IP organization. The role involves owning the architecture, development, integration, and adoption of AI solutions, including ML/LLM models and data pipelines, into EDA workflows and CI/CD systems. The goal is to drive process transformation and enterprise-scale automation for hardware engineering teams.

What you'd actually do

  1. Own the architecture and roadmap for AI-based productivity tools supporting: RTL development, Design verification, IP quality and signoff flows
  2. Design and implement production-grade AI tools for: Regression failure clustering and triage, Intelligent log analysis and anomaly detection, Automated lint/CDC/RDC issue classification, AI-assisted debug and root-cause analysis
  3. Integrate AI solutions into: EDA workflows, CI/CD and regression systems, Version control and review pipelines
  4. Define and maintain data strategies using: Simulation logs, Coverage databases, Static analysis reports
  5. Drive adoption through: Documentation and training, Feedback-driven iterations

Skills

Required

  • Python
  • Machine learning
  • NLP
  • LLM-based systems
  • Data engineering
  • Feature pipelines
  • RTL (SystemVerilog) and UVM concepts
  • EDA tools and flows (lint, CDC, simulation, regressions)
  • Integrating AI tools into large engineering organizations

Nice to have

  • C++ or Java
  • AI copilots for engineering teams
  • Log intelligence and analytics platforms
  • CI/CD systems (Jenkins, GitLab)
  • MLOps platforms
  • IP reuse and signoff processes
  • Security and compliance for internal tools

What the JD emphasized

  • own and drive AI-powered tools
  • production-ready AI solutions
  • production-grade AI tools
  • AI-assisted engineering solutions
  • enterprise-scale automation
  • AI solutions into EDA workflows
  • AI assistants for RTL and DV engineers
  • AI tools into large engineering organizations
  • translate engineering pain points into scalable AI solutions

Other signals

  • AI-powered tools
  • AI-assisted engineering solutions
  • enterprise-scale automation
  • production-grade AI tools
  • AI assistants for RTL and DV engineers
  • AI solutions into EDA workflows
  • MLOps practices