Principal Engineer – Supply Chain Planning

This is a fully remote position, open to applicants in California.

📋 Description

• Develop and establish Quince’s unique supply chain planning platform from inception.

• Design and manage the complete model pipeline lifecycle, which encompasses feature engineering, forecasting tournament framework, evaluation, deployment, monitoring, and refreshing.

• Create a framework for experimentation to facilitate safe production iterations.

• Integrate vendor management, order management, and inventory systems into the planning architecture.

• Establish standards for AI-assisted engineering, incorporating coding assistants, AI-generated tests, and AI-enhanced data exploration.

• Design LLM-supported observability, root-cause analysis, natural-language operator interfaces, and agentic planning workflows.

• Collaborate with the science team on vector stores, prompt versioning, and LLM evaluation tools.

• Develop dashboards, override workflows, audit trails, and alerts for operational users.

• Create observability systems to monitor model drift, data quality issues, and forecasting failures.

• Construct feedback mechanisms using operator overrides to enhance model performance.

• Work with planning teams and business leadership to set priorities and translate business challenges into engineering specifications.

• Determine the technical direction for the planning tools domain and ensure integration with logistics, warehouse, and supply chain systems.

• Offer technical guidance to a globally distributed engineering team.

• Recruit and cultivate a small engineering team.

⛳️ Requirements

• A minimum of 12 years of software engineering experience, with substantial involvement in developing data-intensive, ML-related, or scientific platform systems in a production environment.

• Proven experience in 0-to-1 platform ownership, successfully guiding a greenfield initiative from architecture to production.

• Extensive experience in production ML and AI platform engineering, including feature pipelines, model serving, experimentation frameworks, monitoring, drift detection, vector stores, prompt and trace versioning, and LLM evaluation tools.

• Proficient in AI-native engineering practices, such as code generation, test creation, and AI-enhanced platform functionalities in production.

• Familiarity with forecasting and optimization models adequate for building supporting infrastructure and collaborating with scientists as a technical peer.

• Strong foundational knowledge in software engineering, particularly in data systems, API design, pipeline orchestration, and production operations.

• Excellent communication skills with the ability to convert stakeholder needs into architectural designs and roadmaps.

• Experience in supply chain planning, demand forecasting, inventory optimization, or logistics operations is highly desirable.

• Previous experience in providing technical direction to distributed engineering teams is preferred.

• A hands-on background in ML or data science is an advantage.

🏝️ Benefits

• Bonus and equity options may be available for eligible positions.

• Reasonable accommodations will be made for qualified individuals with disabilities.

• Equal employment opportunities and protections against discrimination are upheld.

• Background checks will be performed in accordance with applicable laws.