About the role

Lead Principal Engineer - AI Domain Expert role based on the published job description. Key responsibilities and requirements were extracted directly from the posting for quick review.

IDMOnsiteATV

Key Responsibilities

AI Architecture & Enterprise Strategy
Define and lead the enterprise-wide AI architecture supporting product development, test engineering, and manufacturing operations.
Build scalable AI ecosystems using LLMs, intelligent agents, token-based workflows, and multimodal data integration.
Drive an AI roadmap focused on effort reduction, efficiency gains, and accelerated engineering throughput.
Shift-Left Product Development & Pre-Silicon Predictive Analytics
Architect AI-driven pre-silicon prediction platforms to identify potential yield, performance, and reliability issues before tape‑out.
Integrate simulation, modelling, RTL/DV data, and historical silicon learning to predict failure modes early.
Influence upstream design, architecture, DFT, and validation teams to make data-informed decisions earlier in the lifecycle, reducing downstream debug cycles.
Silicon Characterization, Test Optimization & Yield Engineering

Requirements

15+ years of semiconductor experience spanning product development, test engineering, silicon bring-up, characterization, and yield engineering.
Deep understanding of the full semiconductor lifecycle:
→ RTL → Design Verification → DFT → pre‑Si modelling -> technology
-up, validation, and characterization
ATE development, OSAT/test operations, system debug
, defect density modelling, parametric analysis
Demonstrated success applying AI/ML techniques in engineering environments
Expertise in:
LLM architectures, embeddings, vector stores
-agent systems and autonomous agent frameworks
Model Context Protocol (MCP) and skills-based AI architecture
Proven ability to deliver production-scale AI solutions that improve cycle time, predictability, and engineering efficiency.
Strong leadership, communication, and cross-functional influence capabilities.