Principal Product Manager, Search
THE ROLE
We're looking for a Product Lead to join our growing team. In this role, you will be responsible for transforming onsite search from a keyword-based utility into an intelligent, personalized discovery engine. In the near term, this role will focus on strengthening data platforms, experimentation, and incremental improvements on top of Algolia. Over time, this person will drive the evolution of search toward semantic, AI-powered, and personalized experiences that differentiate our brand and delight customers. This role plays a critical part in advancing both our team's goals and Quince's broader mission.
Responsibilities
Define and execute the search strategy balancing immediate platform improvements with long-term innovation
Lead data platform and experimentation efforts (data pipelines, dashboards, A/B testing) to enable rapid iteration and insight-driven decision making
Manage and improve current Algolia-based search, focusing on relevance tuning, query handling, and performance optimization
Build roadmap for AI/semantic search evolution (vector-based retrieval, personalized ranking, LLM-assisted discovery)
Partner cross-functionally with data science, data engineering, and ML engineering to deliver next-gen search models and pipelines
Oversee QA, UAT, and signoff for new algorithms, features, and experimentation frameworks before production launch
Champion voice of the customer by translating insights into actionable improvements across search relevance, usability, and speed
Act as an internal thought leader on how AI and semantic technologies can reshape product discovery
Qualifications
Required:
10+ years of product management experience, with 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 (A/B testing, statistical methods, KPI definition) and ability to translate insights into product decisions
Knowledge of machine learning productization: feature stores, inference platforms, model monitoring, and A/B testing of ML-driven systems
Familiarity with search platforms and technologies (e.g., Algolia, Elasticsearch, Solr, OpenSearch) and understanding of their strengths/limitations
Excellent written and verbal communication skills; able to influence cross-functional teams and executive stakeholders without formal authority
Strong analytical mindset; comfortable digging into data and collaborating with engineers/data scientists to answer product questions with evidence
Demonstrated success in defining roadmaps, prioritizing tradeoffs, and delivering high-quality product experiences
Preferred:
Hands-on experience implementing or product managing semantic search, LLM agent-powered features
Track record of personalization initiatives (customer-specific ranking, context-aware search, lifecycle-based recommendations)
Excited by a super-IC role with broad scope and impact, acting as the connective tissue between engineering, data, and business
Pay Range: $200,000-$280,000 + bonus + equity
All posted ranges are reflective of base salary and may vary depending upon experience level and location. Bonus and equity may also be provided for eligible roles.
Pay Range
$250,000—$334,000 USD