Automation Engineer, Manufacturing Automation Design & Engineering
Listed on 2026-06-15
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Engineering
Automation & Mechatronics Engineer, Electrical Engineering, Systems Engineer, Electronics Engineer
Automation Engineer, Manufacturing Automation Design & Engineering
Job : | Amazon Data Services, Inc.
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 RoleYou 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 with industrial controls architecture, turning a mechanical robot into an intelligent quality gate that catches defects at the point of assembly.
Our scope covers all server and rack assembly across all architectures and platforms — compute, AI/ML accelerators, storage, and networking. We design predictive‑analytics‑driven production systems where every station is sensor‑driven, AI‑optimized, and self‑correcting, scaling 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.
- Reduce false call rate 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.
We are building a centralized automation Center of Excellence that owns the process specification and IP for how AWS hardware gets assembled. The Manufacturing Automation Design & Engineering team is responsible for defining automated process requirements, designing and proving solutions at proof‑of‑concept, and maintaining AWS‑owned intellectual property that scales globally. We work within a collaborative framework across Hardware Engineering, Manufacturing Automation Design & Engineering, and Manufacturing Operations to ensure automation is engineered once, proven once, and deployed everywhere.
BasicQualifications
- BS/MS Electrical Engineering, Computer Engineering, Controls Engineering, or equivalent.
- 5+ years in industrial controls AND machine vision/automated optical inspection.
- Proficiency in PLC programming (Allen‑Bradley, Siemens, or Beckhoff).
- Experience with machine vision platforms (Cognex, Keyence, Koh Young, or equivalent).
- Industrial networking experience (Ether Net/IP, Profinet, OPC‑UA).
- Experience designing controls architecture for multi‑site standardization.
- AI/ML‑based defect classification and computer vision model development.
- 4+ years PLC/SCADA integration experience.
- Experience with precision measurement and inspection devices (optical inspection, force sensors, automated gauging).
- MES integration experience (SAP MES, iFactory, or equivalent manufacturing execution systems).
- SPC implementation and statistical process control methods.
- High‑complexity electronics or precision hardware manufacturing experience.
- Experience defining controls standards that replicate across multiple…
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