AI Engineering Architect – Agentic AI & Digital Engineering

To make electronics, you need chips, wafers, transistors, reticles, and... To make these, you must see, test and manufacture them at scale—faster and better than ever before. That's where KLA comes in. Whether you're early in your career or an experienced professional, you'll solve complex challenges, work alongside brilliant minds and help shape the future of technology.

Group/Division The Semiconductor Products and Customers (Semi PC) business unit designs, builds and sells KLA’s product portfolio to help chip manufacturers meet high-quality standards for technologies like AI, data centers, automotive and electronic devices. Our inspection, metrology, and analytics systems detect and monitor defects across logic and memory chips, specialty semiconductors, wafers, reticles, advanced packaging, process equipment and materials. We also develop technologies for specialty processes, IC substrates, and PCB manufacturing, including etch and deposition, component inspection, and imaging and analytics.

The RAPID division leads the industry in reticle inspection solutions, helping ensure high lithography yields and cost-effective semiconductor manufacturing. Its systems support both mask shops and fabs by detecting defects early in the process, enabling faster, more reliable production.

What You'll DoIn this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise.

The Advanced Technology of RAPID Division is seeking a builder-first AI Engineering Architect to define and deploy AI solutions for EUV source development and next-generation actinic inspection engineering. This role will focus on AI roadmap ownership and implementation across tool health analytics, intelligent troubleshooting, agentic workflow automation, AI-augmented MBSE / digital thread, routing/CAD/BOM workflows, and engineering productivity tools.

Why Join / Business Impact:

This role targets current bottlenecks in engineering planning and transformation, including tool health monitoring, root-cause analysis, procedure and document acceleration, digital-thread adoption, and engineering workflow productivity. The goal is to reduce engineering iteration, improve decision quality, and accelerate development readiness for advanced EUV source and actinic inspection systems.

Key Responsibilities Own the AI roadmap for EUV source and digital engineering use cases; identify, prioritize, and sequence high-value opportunities tied to engineering impact.

Build AI solutions for source health analytics, anomaly detection, and predictive monitoring using engineering telemetry, metrology, and operational data.

Develop AI-assisted and agentic workflows for alarm audit, root-cause analysis, procedure creation, and engineering task automation.

Partner with engineering teams to enable AI-assisted modeling, digital thread, MBSE, and knowledge-grounded engineering workflows.

Support AI-assisted routing, CAD integration, model-to-BOM, and early BOM activities as part of engineering digital transformation.

Define AI observability, evaluation, tracing, and safe production deployment practices for engineering AI systems.

Preferred Qualifications

Experience with agentic AI, tool-using LLM workflows, multi-agent systems, or RAG/vector-backed knowledge systems.

Experience with time-series forecasting, anomaly detection, or predictive analytics for industrial systems.

Experience with MBSE, digital thread, SysML, requirements traceability, or model-centric engineering.

Experience with CAD/PLM/PDM integration, BOM workflows, or engineering data interoperability.

Experience in semiconductor equipment, capital equipment, optics, plasma, vacuum systems, or manufacturing engineering.

Minimum Qualifications …