Network Design & Speed PM II, Fulfillment Experience

We're looking for a PM who can think in networks — nodes, lanes, flows, and tradeoffs — to help us build the fastest, leanest fulfillment topology in Mexico. You'll own the analytical backbone of our network design decisions: where to place capacity, which lanes to activate or kill, how to route middle-mile to hit speed targets, and how topology changes ripple through cost and delivery promises.

This isn't a coordination role. You'll build models, run scenarios, and come to the table with recommendations that shape how millions of packages flow from fulfillment centers to customers' doors. You'll work at the intersection of supply chain engineering, transportation planning, and delivery speed — translating demand patterns and operational constraints into concrete infrastructure proposals.

If you get excited about optimizing a network graph, debating lane economics, or finding the CPT configuration that unlocks next-day coverage for a new city — this is your role.

Key job responsibilities
- Design and evaluate network topology scenarios (node placement, lane structure, sort-code routing) using data-driven models to optimize speed, cost, and capacity tradeoffs.
- Own the analytical pipeline for middle-mile network planning: build capacity models, run what-if simulations, and produce recommendations for lane activations, deprecations, and volume rebalancing.
- Develop and track delivery speed improvement plans with clear month-over-month targets, identifying root causes of speed drag and proposing structural network fixes.
- Partner with Operations, Transportation, and Last-Mile teams to validate design proposals against real-world constraints (vehicle capacity, sort windows, CPT cutoffs).
- Present network design recommendations to senior leadership with clear logic, supporting data, and implementation roadmaps.
- Monitor network performance post-implementation and iterate on designs based on actual volume flow and speed outcomes.

A day in the life
You start with fresh speed and capacity data — checking which lanes are over-utilized, where delivery promises are slipping, and what volume shifts happened overnight. Mid-morning you're running topology scenarios: what happens if we add a direct lane from SC X to DS Y? Does it hit the speed target without blowing cost? After lunch you're in a review with Ops and Transportation, pressure-testing your proposal before it goes to leadership. By end of day you're updating your network model with new inputs and prepping the recommendation deck for next week's planning cycle.

About the team
We're the Fulfillment Experience (FX) team — the group that designs how Amazon MX's supply chain actually works. We own network strategic design, transportation planning, and the systems that orchestrate every customer order from fulfillment center to front door. Our mission: deliver every package at the fastest speed, lowest cost, and highest reliability possible. We're a mix of engineers, PMs, and analysts who geek out on network optimization and aren't afraid to challenge the status quo. If you want your work to directly shape infrastructure that serves millions of customers, this is the team.

Basic Qualifications

- 3+ years of program or project management experience
- 3+ years of working cross functionally with tech and non-tech teams experience
- 3+ years of defining and implementing process improvement initiatives using data and metrics experience
- Knowledge of Excel (Pivot Tables, VLookUps) at an advanced level and SQL
- Experience defining program requirements and using data and metrics to determine improvements
- Speak, write, and read fluently in English
- Bachelor's degree

Preferred Qualifications

- 3+ years of driving end to end delivery, and communicating results to senior leadership experience
- 3+ years of driving process improvements experience
- Experience in stakeholder management, dealing with multiple stakeholders at varied levels of the organization
- Experience building processes, project management, and schedules

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