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.
Key job 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
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