Drimva

Amazon

Integration & Deployment Supply Chain Manager, One MHS

$108K–$162K

Austin, TX +4 · Manager · Full-time · Posted Sep 1, 2026

Location
Austin, TX
Nashville, TN
Bellevue, WA
Atlanta, GA
Springdale, OH
Experience
5+ years in a listed supply chain or program management area; 5+ years with inventory management systems.
Education
Bachelor's degree in supply chain management, operations, engineering, analytics, or related field.

About the job

Owns end-to-end material planning and operations for concurrent material handling system installation programs, ensuring materials are forecast, tracked, delivered, and staged to match deployment schedules.

What you'll do

  • Develop material sequencing strategies, demand forecasts, kitting priorities, and delivery and staging workflows aligned with installation schedules.
  • Coordinate procurement, vendor, logistics, and field-site material flows; manage inventory visibility and mitigate supply and delivery risks.
  • Implement inventory systems and material operations technology, and improve performance through analytics, automation, and AI-enabled forecasting.

What they ask for

  • 5+ years of supply chain management, planning, strategic sourcing, commodity management, or program management experience.
  • Bachelor's degree in supply chain management, operations, engineering, analytics, or a related field.
  • Experience managing and coordinating multiple projects simultaneously.
  • 5+ years of experience with inventory management systems (WMS, ERP, or equivalent).

Nice to have

  • Master's degree in engineering, mechanical, operations, supply chain, business administration, or an equivalent STEM field.
  • Experience with Lean Management, Six Sigma, analytics or demand forecasting, BI tools, industrial deployment, or warehouse automation.

Pay

119,600.00 - 161,700.00 USD annually (base salary); 107,600.00 - 145,600.00 USD annually (base salary)

Tools

WMS, ERP, RFID/BLE, Quick Sight, Tableau, Power BI

AI focus

Uses AI-enabled forecasting and tools to improve demand accuracy, reduce material-driven schedule risk, and scale deployments.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)