Principal Product Manager, Search

Quince•Palo Alto, CA

15h•$250,000 - $334,000

About The Position

Quince is seeking a Product Lead to transform onsite search from a keyword-based utility into an intelligent, personalized discovery engine. Initially, the role will strengthen data platforms and experimentation and deliver incremental improvements to the existing Algolia-based search experience. Over time, the role will lead the evolution toward semantic, AI-powered, and personalized search experiences that differentiate the brand and improve customer discovery. The position contributes to the product team’s goals and Quince’s broader mission.

Requirements

At least 10 years of product management experience, including at least 7 years working closely with data science, ML, or search/information retrieval teams.
Proven track record of shipping and scaling customer-facing data science or search products with measurable business impact.
Strong foundation in experimentation, including A/B testing, statistical methods, and KPI definition, and ability to translate insights into product decisions.
Knowledge of machine learning productization, including feature stores, inference platforms, model monitoring, and A/B testing of ML-driven systems.
Familiarity with search platforms and technologies such as Algolia, Elasticsearch, Solr, or OpenSearch, and understanding of their strengths and limitations.
Excellent written and verbal communication skills, with the ability to influence cross-functional teams and executive stakeholders without formal authority.
Strong analytical mindset and comfort working with data and collaborating with engineers and data scientists to answer product questions with evidence.
Demonstrated success defining roadmaps, prioritizing tradeoffs, and delivering high-quality product experiences.

Nice To Haves

Hands-on experience implementing or product managing semantic search or LLM agent-powered features.
Track record of personalization initiatives, such as customer-specific ranking, context-aware search, or lifecycle-based recommendations.
Enthusiasm for a super-IC role with broad scope and impact, connecting engineering, data, and business.

Responsibilities

Define and execute search strategy, balancing near-term platform improvements with long-term innovation.
Lead data platform and experimentation efforts, including data pipelines, dashboards, and A/B testing, to support rapid iteration and insight-driven decisions.
Manage and improve Algolia-based search, including relevance tuning, query handling, and performance optimization.
Build a roadmap for AI and semantic search evolution, including vector-based retrieval, personalized ranking, and LLM-assisted discovery.
Partner with data science, data engineering, and ML engineering to deliver next-generation search models and pipelines.
Oversee QA, UAT, and signoff for new algorithms, features, and experimentation frameworks before production launch.
Represent the voice of the customer by translating insights into improvements to search relevance, usability, and speed.
Act as an internal thought leader on how AI and semantic technologies can reshape product discovery.