Senior Principal Engineer, AI & Data Platform

Job Summary

We are seeking a Senior Principal Engineer to architect and lead the company-wide AI and data infrastructure powering our Data & AI Transformation initiatives. This role will own the architecture for data and AI across design, R&D, manufacturing, and business functions, including in-house MES and ERP systems, turning data into insights that improve product development, yield, cost, and operational performance.

We are an AI-native team, using agentic workflows and AI-assisted development to build quickly while keeping line-critical decisions deterministic and auditable. This role sets the technical direction that keeps that pace sustainable at scale, defining the architecture, standards, and deployment paths that every AI solution is built on.

You will work closely with design, R&D, engineering, manufacturing, quality, planning, supply chain, and finance teams, as well as senior leadership, to translate business priorities into a scalable, secure, and production-ready platform shared across the company. This is a hands-on technical leadership role, combining architecture ownership with direct contribution to design, code, and review.

Job Responsibilities

• Define and own the company-wide architecture for AI and data infrastructure, spanning data acquisition, storage, processing, applications, and AI services across on-premise and cloud.
• Architect and maintain data platforms that collect, standardize, and govern large volumes of design, simulation, manufacturing, test, and business data across all sites.
• Build shared AI infrastructure and MLOps for all teams, including experiment tracking with MLflow, model training and serving, LLM services, agent runtimes, and simulation compute.
• Lead the design and development of in-house MES and ERP systems, covering work-in-progress tracking, lot and unit traceability, production planning, inventory, and quality records.
• Build data integration across design tools, testers, equipment, enterprise systems, and vendors through APIs, file exports, and equipment communication standards such as SECS/GEM.
• Lead analytics and AI solutions that extract insights across the company, including design automation, yield and test analytics, operational reporting, and supply chain visibility.
• Architect and operate AWS and on-premise infrastructure with DevOps practices, including infrastructure-as-code, CI/CD, containers, networking, and hybrid connectivity across sites.
• Build high-performance services and applications using Rust, TypeScript, and Python, and set the standards for code quality, testing, reliability, and documentation.
• Ensure data integrity, security, access control, and traceability across all systems, supporting intellectual property protection, quality requirements, and customer audits.
• Partner with senior leadership and teams across the company to define the platform roadmap, guide build-versus-buy decisions, and mentor engineers through design and code reviews.

Requirements

• 15+ years of experience in semiconductor software and data engineering, with a Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• Proven track record architecting enterprise data platforms that manage large volumes of design, manufacturing, test, and business data across multiple sites.
• Hands-on experience designing and building MES, ERP, or related enterprise systems, including integration with design tools, equipment, testers, and business applications.
• Strong programming skills in languages such as Rust, TypeScript, and Python, with deep experience in SQL databases, data modeling, distributed systems, and API design.
• Extensive experience with AWS, DevOps, and MLOps, including technologies such as Docker, Kubernetes, Terraform, CI/CD pipelines, and MLflow.
• Experience deploying AI/ML or LLM solutions into production, with daily use of AI-assisted development tools such as Claude Code, Codex, or Cursor.

Skills

Business Data Analysis, Lead Management, Applications, Computer Engineering, Azure DevOps, AWS, Business Information, Development Tools, Design Tools, Business Intelligence architecture, Design database architectures, Cross Functional Team Building, Implementing Erp Solutions, enforces coding standards, Docker Container, data integration projects