Infineon Technologies

Lead Principal Engineer - AI Domain Expert

Infineon Technologies
Integrated Device ManufacturingSingaporeOnsitePosted 3 weeks ago

About the role

AI summarised

Lead the enterprise-wide AI architecture and strategy to drive significant efficiency gains across product development, test engineering, and manufacturing operations within the semiconductor lifecycle. This role involves building scalable AI ecosystems using LLMs and intelligent agents to enable predictive analytics, optimize silicon characterization, and accelerate product ramp cycles.

IDMOnsiteATV

Key Responsibilities

  • Define and lead the enterprise-wide AI architecture supporting product development, test engineering, and manufacturing operations.
  • Build scalable AI ecosystems utilizing LLMs, intelligent agents, token-based workflows, and multimodal data integration to drive the AI roadmap.
  • Architect AI-driven pre-silicon prediction platforms integrating simulation, modeling, and historical silicon learning to predict failure modes early.
  • Drive AI systems for silicon characterization, defect density analysis, adaptive test optimization, and yield ramp acceleration.
  • Lead the integration of heterogeneous datasets (design, fab, OSAT, system test) into unified, AI-ready data platforms.
  • Drive and enable autonomous engineering assistants for automated data analysis, debug triage, pattern detection, and decision recommendations.
  • Act as a senior technical authority, influencing strategic direction across design, manufacturing, and product engineering teams.

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: architecture → RTL → DV → DFT → pre-Si modelling -> validation and characterization.
  • Demonstrated success applying AI/ML techniques within engineering environments.
  • Expertise in LLM architectures, embeddings, vector stores, multi-agent systems, and autonomous agent frameworks.
  • Proven ability to deliver production-scale AI solutions that improve cycle time, predictability, and engineering efficiency.
  • Strong leadership, communication, and cross-functional influence capabilities.