Senior Engineer, AI & Data Platform

Position Overview

We are seeking a Senior AI & Data Platform Engineer to build and operate the technical foundation for our Data & AI Transformation initiatives, owning the manufacturing data platform, infrastructure, equipment data integration, AI infrastructure, MLOps, and agentic systems that improve testing, yield, and cost. This hands-on, end-to-end role works closely with engineering, manufacturing, and planning teams to turn real-world challenges into reliable, production-ready software and AI solutions, from architecture and development through deployment, monitoring, and continuous improvement, while ensuring critical manufacturing decisions remain deterministic, auditable, and scalable.

Job Responsibilities

• Build and operate AI/ML infrastructure, including data pipelines, model training, LLM serving, retrieval systems, agent runtimes, evaluation, and monitoring.
• Own production infrastructure across factory and cloud environments, including Linux, Docker, GPUs, CI/CD, networking, and infrastructure-as-code.
• Develop scalable manufacturing data platforms and ingestion pipelines integrating tester, equipment, vendor, and reporting data.
• Build backend services, APIs, applications, and automation using Python and modern web technologies.
• Deploy and operate AI/LLM solutions, including agentic workflows for manufacturing reporting, log analysis, and natural-language data querying.
• Establish robust engineering practices across testing, monitoring, version control, documentation, and continuous deployment.
• Collaborate with vendors and internal teams to integrate systems and translate manufacturing needs into solutions that improve yield, efficiency, cost, and operations.

Requirements

• 4+ years of software engineering experience, with strong Python skills.
• Strong SQL, database, ETL, and data pipeline experience, including PostgreSQL or MySQL.
• Production infrastructure experience with Linux, Docker, CI/CD, and AWS, Azure, or GCP.
• Backend and AI/ML infrastructure experience with technologies such as FastAPI, Flask, Django, vLLM, MLflow, LangGraph, or MCP.
• Hands-on experience deploying AI/ML and LLM solutions, including agentic workflows, with proven use of AI-assisted development tools such as Claude Code, Codex, or Cursor to deliver production software.