Additional Information
Amazon Web Services' Hardware Engineering team is looking for experienced professionals to help build the world's premier cloud computing platform. Our Manufacturing Automation Design & Engineering team designs, validates, and deploys automation solutions - robotics, cobots, vision inspection, AI-powered quality systems, and automated assembly workflows - across contract manufacturer sites worldwide.
About the Role: You will architect the controls backbone and intelligent inspection strategy that makes every automated station self-verifying. This means defining how PLCs, sensors, cameras, AOI algorithms, and MES data connections integrate across every automation cell - creating a standardized, replicable controls and inspection package that deploys across all CM sites without re-engineering. You combine deep expertise in machine vision (AI-based defect classification, force sensing, AOI model training) with industrial controls architecture (PLC platforms, safety systems, network protocols). Your work turns a mechanical robot into an intelligent quality gate - catching defects at the point of assembly rather than at test or in the datacenter.
Our scope covers all server and rack assembly across all architectures and platforms - compute, AI/ML accelerators, storage, and networking. We design intelligent, predictive-analytics-driven production systems where every station is sensor-driven, AI-optimized, and self-correcting - turning assembly lines into programmable, data-generating platforms that scale capacity without scaling headcount.This role requires the engineer to operate in a fast-paced, multi-platform international manufacturing environment with travel to contract manufacturer sites (up to 25-30% travel anticipated).
Key job responsibilities
- Architect controls standard for all automation cells: PLC platform selection, network protocol, sensor architecture, safety system design
- Develop and optimize AOI inspection programs per product - validated, version-controlled, transferable across sites
- Drive false call rate reduction through iterative program tuning and AI-assisted defect classification
- Design sensor integration architecture connecting automation equipment to MES (iFactory) for 100% digital traceability
- Create standardized controls packages (PLC logic + HMI + sensor configs) replicable across all CM sites
- Perform equipment qualification, Gage R&R studies, and acceptance testing for vision/inspection systems
- Define controls safety architecture (E-stops, interlocks, light curtains) per ISO 13849 / IEC 62443
- Partner with Central Quality on inspection acceptance criteria and with MES teams on data integration requirements
Amazon Data · Salt Lake City, UT