Ai Automation Engineer Jobs in Spring, TX (NOW HIRING)

Amazon Web Services' Hardware Engineering team is looking for experienced professionals to help build the world's premier cloud computing platform. The Manufacturing Automation Design & Engineering team designs, validates, and deploys automation solutions, including robotics, cobots, vision inspection, AI-powered quality systems, and automated assembly workflows, across contract manufacturer sites worldwide.
About the Role: You will own the manufacturing data architecture and MES integration strategy that connects automated production equipment to enterprise systems across all contract manufacturer sites. You design and deploy the data infrastructure layer that enables every automated station to generate, transmit, and store production data in a standardized format

You configure and integrate MES platforms with automation equipment (PLCs, robots, vision systems, sensors), define recipe management structures for multi-platform production, and establish industrial communication protocols (OPC-UA, MQTT, EtherNet/IP) as the standard data transport layer. You build production data pipelines that feed traceability systems, SPC monitoring, and process drift detection, providing the engineering team with real-time visibility into automation performance. You define data schemas and integration standards that ensure manufacturing data is consistent across all contract manufacturers, enabling the team to compare, benchmark, and optimize automation across sites.

You also own the integration of manufacturing production data with SAP systems, ensuring automated assembly data (production orders, material consumption, yield, and traceability records) flows into the enterprise ERP layer for planning, costing, and compliance.
The scope covers all server and rack assembly across all architectures and platforms, including compute, AI/ML accelerators, storage, and networking. The team designs 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
Own the MES integration architecture: defining how automation equipment (PLCs, robots, vision, sensors) connects to MES and enterprise data systems at all contract manufacturer sites
Design and deploy industrial data pipelines from production equipment to centralized data platforms using OPC-UA, MQTT, and EtherNet/IP protocols
Configure MES platforms for automated production lines: recipe management, work order routing, process parameter tracking, and production event logging
Define data schemas and standards that ensure manufacturing data consistency across all contract manufacturers and platforms
Build production traceability systems linking every automated operation (torque, inspection result, cycle time) to the individual assembled unit
Implement SPC monitoring and automated alerting for process drift detection across automated stations
Define and deploy industrial communication protocol standards for the automation ecosystem
Partner with Controls and Vision engineers to ensure all automation cells output data in the defined standard format
Integrate manufacturing production data with SAP (production orders, material consumption, quality results, yield reporting) to enable enterprise-level planning, costing, and traceability
About the team
About the team: The Manufacturing Automation Design & Engineering team is building a centralized automation Center of Excellence that owns the process specification and IP for how AWS hardware gets assembled

The team is responsible for engineering, defining automated process requirements, designing and proving solutions at proof-of-concept, and maintaining AWS-owned intellectual property that scales globally. The team works within a collaborative framework across Hardware Engineering (product design for automation), Manufacturing Automation Design & Engineering (process specification and validation), and Manufacturing Operations (deployment and scaling), ensuring automation is engineered once, proven once, and deployed everywhere.