You will build the optimization brain for Amazon's externalized logistics network — a system that couples first-mile route planning with middle-mile network optimization into a joint iterative loop, producing end-to-end recommendations that no single optimizer can reach alone. The technical challenge is real: solvers that take hours per run, a combinatorial search space that defies brute-force, model gaps that require deep-diving into solver internals, and convergence that must be proven across independently owned engines. This is not a scale or latency problem — it's a multi-system optimization convergence problem where you invent the pruning, approximation, and coupling strategies. Your recommendations will directly shape commercial decisions — which shippers to pursue, which geographies to grow, which contracts to reprice — giving this role rare direct business impact for a PE position. In addition, you will provide tech leadership to the fulfillment charter for Amazon Shipping where you will be responsible for increasing the label conversion rates that would be a key enabler for revenue growth; identify solutions such as dynamic network capacity management to build a resilient network topology; identify and build speed opportunities in the upstream planning systems; and solve unique challenges related to delivery addresses for an externalized supply chain business where orders are created outside amazon marketplace. You will also be responsible for architectural integrity and scalability of fulfillment systems by (1) identifying interface contracts with partner tech teams (2) making the architecture more nimble and self-serve for faster time-to-market of new capabilities (3) improving resiliency and availability of Tier-1 systems (4) optimizing the level of service orchestration within the fulfillment systems. Responsibilities Architect the joint FM-MM optimization loop: state-passing contracts, convergence detection, parallel execution, and checkpoint/restart Solve computational tractability through smart pruning, lightweight solvers, and metaheuristic search at network scale Drive cross-org alignment across 5+ organizations — securing stable interfaces and committed roadmap items Translate optimization outputs into actionable recommendations for Operations (node mapping, capacity), Commercial (shipper targets, geographies), and Finance (cost-to-serve, contract economics) Mentor a team of Applied Scientists and SDEs; set technical bar and build experimentation culture Define and execute the phased roadmap: FM cost optimizer (Phase 1) → joint FM-MM optimizer (Phase 2) → decision engines that close the loop from network optimization to commercial strategy (Phase 3) Own system validation and accuracy: design feedback loops from actual vs. predicted outcomes, detect degradation, and define refresh cadence 12+ years of software development with increasing scope; 7+ years in system architecture Demonstrated ability to take ambiguous problem spaces — where requirements, success metrics, and solution approach are all undefined — and drive them to concrete technical strategy and execution Experience communicating with technical teams, business stakeholders, and leadership to collect requirements, describe technical designs, and align on product strategy Track record of influencing technical direction across 5+ partner organizations without direct authority Experience mentoring senior engineers and scientists Experience building decision-support systems adopted by non-technical stakeholders M.S./Ph.D. in Operations Research, CS, Applied Math, or related field Expertise in logistics optimization: vehicle routing, network design, or supply chain planning at scale Deep expertise in optimization systems, operations research, or simulation — building production systems that solve combinatorial optimization or search problems Experience with iterative optimization or metaheuristic frameworks in production Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
