Senior Product Manager - AI, Search and Personalization

Nuuly; Philadelphia (Philadelphia County); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical

Dental

Vision

PTO

Employee discounts

Retirement savings

Job summary

Nuuly is seeking a Senior Product Manager to lead features bridging product discovery, merchandising, and AI to help customers find what they love. You will own experiences connecting customers to items via onsite search, browse, and personalization, working with Merchandising, Inventory Science, UX, Marketing, and Data Science to translate business needs into technical requirements.

The role requires deep knowledge of apparel product data, search relevance, and LLM-driven workflows, with a

Qualifications

• 5–8 years in product management within SDLC (software development lifecycle) environment, ecommerce or subscription-based platforms preferred.
• Knowledge of retail product data and attribution, particularly in apparel.
• Experience defining requirements for onsite search, including relevance and query tuning, and for recommendation engines or personalization.
• Familiarity with how search and recommendation performance is measured (e.g., click-through, conversion, zero-result rate).
• Experience writing and testing LLM prompts used in automated workflows, and knowledge of AI tool integration concepts (MCP, connectors, agentic workflows).
• Ability to identify opportunities where AI can drive efficiency improvements.
• Experience writing requirements for REST services and working in a microservices environment.
• Strong documentation and technical writing skills.
• Working knowledge of SQL; experience with JIRA and Confluence
• Effective communication across technical and non-technical audiences; comfortable working in Agile Scrum environments with cross-functional teams
• Experience with BigQuery, automated API testing (Karate, Postman, etc.), or Kafka and other event-driven architecture a plus

Responsibilities

• Own discovery features end-to-end, from problem definition and scope through launch, measurement, and iteration, balancing customer experience, effort, scalability, and performance.
• Partner with Merchandising, Inventory Science, UX, Marketing, and Data Science to gather, prioritize, and translate business needs into technical requirements.
• Define requirements for the product data and attribution needed to power search, filtering, recommendations, and personalization; identify data gaps and drive their resolution.
• Define search relevance requirements, including query intent, synonyms, ranking rules, and merchandising boosts; set acceptance criteria and evaluate query tuning results with Engineering.
• Define requirements for recommendation and personalization features, including inputs, business rules, placements, and success metrics.
• Write and test LLM prompts used in automated workflows, such as attribute enrichment, product descriptions, and query understanding; define evaluation criteria and acceptance thresholds for their output.
• Lead refinement sessions, collaborate with the delivery team to prioritize sprint work, and participate in the release cycle with DevOps, QA, and Engineering to validate new services, data, and configuration.
• Define success metrics for discovery features and use performance data to guide prioritization.
• Meet with stakeholders regularly to report status and gather new requests, and mentor other members of the Product team

Skills

Product management

SDLC

Agile Scrum

AI/LLM workflows

SQL

REST APIs

Communication

Tools

JIRA

Confluence

BigQuery

Kafka

Postman

Job description

Nuuly is seeking a Senior Product Manager to lead features bridging product discovery, merchandising, and AI to help customers find what they love. You will own experiences connecting customers to items via onsite search, browse, and personalization, working with Merchandising, Inventory Science, UX, Marketing, and Data Science to translate business needs into technical requirements.

The role requires deep knowledge of apparel product data, search relevance, and LLM-driven workflows, with a