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Principal Engineer - Supply Chain Planning

Quince· Forecasting and Planning Engineering
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Remote$265k - $300kFull-timePosted 2mo ago

About the role

Principal Engineer role responsible for building Quince’s AI-native, production-grade supply chain planning platform from scratch, coordinating forecasting, optimization, and operations across multiple vendors, fulfillment centers, and markets.

Responsibilities

  • AI native Platform Architecture & Build - Architect and build Quince’s proprietary supply chain planning platform from the ground up to be multi-vendor, multi-modal, multi-market, and built to scale. - Design and own the full model pipeline lifecycle, including feature engineering, forecasting tournament framework, evaluation, deployment, monitoring, and refresh, and the experimentation framework that lets scientists iterate safely in production. - Build integrations with vendor management, order management, and inventory platforms so the planning system sits at the center of the weekly ordering cadence - Set the standard for how the team builds with AI — coding assistants, AI-generated tests, AI-augmented data exploration — and hold the line on quality of AI-generated output through review rigor and refactoring. - Architect AI-augmented capabilities directly into the platform: LLM-aided observability and root-cause analysis, natural-language operator interfaces over planning data, agentic workflows for routine planning tasks. - Partner with the science team on the infrastructure that AI-driven models need, such as vector stores, prompt versioning, and evaluation harnesses for LLM-based components, so AI-driven science can run reliably in production alongside statistical and ML approaches.
  • Operator Tooling - Build the operator-facing layer that makes the platform usable: dashboards, override workflows, audit trails, and alerts that translate model outputs into decisions a planner can act on - Design observability systems that surface model drift, data quality issues, and forecast failures before they propagate into bad orders or stock-outs - Build the feedback loops that let operator overrides inform and continuously improve future model performance
  • Business Stakeholder Partnership - Work directly with Quince’s planning team and business leadership as a thought partner, synthesizing their operational expertise with your engineering judgment to determine what to build and in what sequence. - Translate business problems, such as in-stock gaps, demand volatility, vendor reliability, and fulfillment split rates, into precise engineering specifications. - Educate stakeholders on system capabilities and trade-offs, building the trust that lets automation and human judgment work in genuine partnership
  • Technical Leadership - Set the technical direction for the planning tools domain, making architectural decisions that scale with Quince’s trajectory across geographies and order-of-magnitude growth - Partner with engineering teams across logistics, warehouse, and supply chain infrastructure to ensure the planning platform integrates cleanly into the broader ecosystem - Provide technical direction to a globally distributed engineering team, establishing architecture and standards that engineers across geographies can execute within - Recruit and grow a small, elite team around you as the charter expands

Qualifications

  • 12+ years of software engineering experience with significant time building data-intensive, ML-adjacent, or science platform systems in production.
  • Demonstrated 0-to-1 platform ownership, taking a greenfield charter from architecture through production at the pace a fast-growing business demands.
  • Strong production ML and AI platform engineering experience: feature pipelines, model serving, experiment frameworks, monitoring, drift detection, and the infrastructure modern AI-driven systems need (vector stores, prompt and trace versioning, LLM evaluation harnesses).
  • AI-native engineering practice. You can speak specifically to where AI tooling has changed how you ship, such as code generation, test authoring, and AI-augmented platform features you've put into production, and where you held quality standards against AI assistance because review rigor was needed.
  • Science literacy as a collaborator; you understand forecasting and optimization models well enough to build great infrastructure around them and partner with scientists as a technical peer.
  • Strong software engineering fundamentals across the full stack: data systems, API design, pipeline orchestration, and production operations
  • Strong communication skills, able to work closely with business and product stakeholders to understand requirements, and translate it into an architectural blueprint and roadmap

Skills

Required:Software engineeringData science / ML in production
Nice to have:AI-native tooling and practices
Last updated Sep 23, 2026. Interested? Apply on the company site.
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About Quince

High Quality Essentials, Radically Low Prices

Quince brings luxury products like Mongolian Cashmere, Italian Leather, Turkish Cotton and Washable Silk to everyone at radically low prices. Shop premium essentials with no middleman.

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