About the role
AI summarisedLead Principal Engineer responsible for defining enterprise-wide AI architecture and driving predictive analytics solutions across the semiconductor lifecycle, from pre-silicon development to manufacturing and test optimization.
IDMOnsiteATV
Key Responsibilities
- Define and lead enterprise-wide AI architecture supporting product development, test engineering, and manufacturing operations using LLMs and intelligent agents
- Architect AI-driven pre-silicon prediction platforms to identify potential yield, performance, and reliability issues before tape-out
- Develop AI systems for silicon characterization correlation, defect density modeling, and parametric variation analysis
- Drive adaptive test, test time reduction, and yield ramp acceleration using autonomous AI agents
- Ensure compliance with AEC-Q100 and ISO 26262 standards for manufacturing readiness
- Deploy AI workflows and autonomous engineering assistants for automated data analysis, debug triage, and report generation
- Integrate heterogeneous datasets from design, fab, OSAT, and operations into unified AI-ready data platforms
Requirements
- 15+ years of semiconductor experience spanning product development, test engineering, and silicon bring-up
- Deep understanding of the full semiconductor lifecycle including architecture, RTL, DV, DFT, and characterization
- Expertise in LLM architectures, embeddings, vector stores, and multi-agent systems
- Proven ability to deliver production-scale AI solutions that improve cycle time and engineering efficiency
- Experience with Model Context Protocol (MCP) and skills-based AI architecture
- Familiarity with ATE platforms including Teradyne, Advantest, or LTX-Credence
- Knowledge of enterprise AI systems and heterogeneous data integration within advanced manufacturing environments
- Experience with cloud and distributed compute systems for AI workloads
- Background with EDA tools, technology development, or yield engineering