Senior Supply Chain Manager, Network Strategy & Planning — Amazon · San Diego, CA. Eight years turning logistics complexity — capital, capacity, cross-functional execution — into governed, repeatable systems, and increasingly, into AI-built software that runs those systems end to end.
Governance, roadmap prioritization, investment planning, operating model design, annual & long-range planning, launch readiness.
Agentic AI, generative AI, workflow automation, decision support systems, operational tooling, product operating models.
Capital portfolio management ($4B+), business case development, forecasting, resource allocation, multiyear budget governance.
Executive stakeholder management, matrixed org alignment, team development, organizational transformation.
Python, SQL, AI/ML, Tableau, QuickSight, Advanced Excel (VBA), SAP, Salesforce, AutoCAD & Revit, ProModel & Crystal Ball, MOST/MTM, simulation & optimization modeling.
Pickup, delivery, and returns planning across Amazon's last-mile network still relied on manual program-management overhead to turn data into decisions — slow to update and hard to scale as volume grew.
Designed and built multiple software products end-to-end (UX and backend architecture), using Agentic AI and Generative AI to replace manual workflows with structured data and intelligent decision systems.
Forecast accuracy and planning speed both improved while the manual workload behind them shrank.
Annual and long-range planning, roadmap alignment, and resource allocation spanned 100+ fulfillment and logistics facilities across North America and the UK, with no standardized governance model.
Designed the operating model for cross-functional portfolio execution — governance cadences (WBR/MBR/QBR), standardized reporting, launch-readiness criteria, and decision-escalation paths — plus the investment business cases and risk assessments behind it.
Standardized effectiveness across 5 organizations and 1,000+ users in NA and the UK.
Automated and manual fulfillment centers across North America had no shared portfolio management framework — asset deployment and labor planning were tracked manually, facility by facility.
Built and owned the operating model and portfolio management framework from scratch — optimization models, labor planning logic, and performance dashboards for asset deployment across the network.
Manual tracking replaced by structured data and standardized reporting network-wide.
I use AI-assisted engineering to go from a math problem to a deployed, production system — solo, end to end. This is one running live right now, not a mockup.
A warehouse slotting optimization platform — the optimization math, the simulation engine, the database, and the security model, designed and shipped solo with AI-assisted engineering.
Compares generic (random) putaway against AI-optimized velocity- and multi-factor slotting for SMB, Mid-Market, and Enterprise warehouse operations — then proves the result with a real discrete-event simulation of a working shift, not just a static estimate.
Multi-objective weighted assignment across travel distance, labor time, congestion, replenishment effort, space utilization, and slot stability — with hard constraints (weight, capacity, zone) and turn-affinity clustering from uploaded historical order data.
A discrete-event shift simulation (binary min-heap event queue) modeling order arrivals, picker travel, and forklift replenishment minute-by-minute — validating the optimization's static KPIs against real time-based behavior.
Postgres via Supabase, with Row-Level Security enforcing a real admin boundary server-side — not a client-side check — behind a self-service admin dashboard and cross-user usage analytics.
What-if scenario testing (demand shifts, zone dedication) and a plain-English trade-off report that translates the math into "move N SKUs, X% less walking, ~Y-day payback" for a non-technical stakeholder.
Optimization math validated against real public grocery transaction data and synthetic Zipf-distributed demand before shipping.
Currently: Senior Supply Chain Manager, Network Strategy & Planning at Amazon. Previously: Sr. Supply Manager & Engineering Manager (Industrial Design Engineering, Amazon), Walmart, Ranir, Amazon India.
Director of Community Outreach (2026–present) — leads PM education, mentorship, and certification outreach across Southern California.
108+ reviews as a judge for the Stevie Awards (Technology, Analytical & Software Engineering) and Global Recognition Awards; active IEEE peer reviewer.
IEEE (Senior Member application under review), INFORMS (presenter, 2026 Annual Meeting), PMI (PMP, PMI-ACP).
Based in San Diego, CA — open to conversations on technology operations, portfolio strategy, and AI-enabled decision systems.