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Product Manager, Agentic AI Tools

URBN (Urban Outfitters, Anthropologie Group, Free People & Nuuly)

Philadelphia, Panama · Full Time

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Experience
3+ yrs
Salary
Openings
1
Posted
4 days ago
Work mode
In office
Eligibility
Open to candidates with relevant product management experience and hands-on exposure to generative AI, especially those who can operate effectively in ambiguity and collaborate across technical and creative functions. Experience in fashion, retail, or consumer products is a plus.
Resume
Required to apply

Where you'll work

Job description

Role overview

URBN is looking for a Product Manager to spearhead a portfolio of agentic AI tools that help internal teams work with more creativity, stronger execution, and higher accuracy. This position is responsible for shaping the product direction and delivering generative AI solutions that accelerate the company’s internal product workflow.

You will work closely with business partners and collaborate every day with AI-focused data scientists and engineers to convert advanced model capabilities into practical, production-ready tools. The role calls for someone who can turn complex and evolving AI possibilities into clear, step-by-step product plans, with a strong focus on shipping incremental value.

The ideal candidate is both detail-driven and imaginative, strategic and decisive. Success in this role requires comfort with cross-functional teamwork, strong data awareness, and deep understanding of generative AI use cases. This is a chance to help reshape how fashion brands create, visualize, and present products.

Responsibilities

  • Own the discovery, build, and launch of GenAI-enabled capabilities with strong accountability and a clear sense of direction.
  • Partner across Engineering, Data Science, Creative, and Merchandising teams to define and align priorities around customer and business impact.
  • Assess new GenAI tools and models carefully, weighing output quality, workflow compatibility, image cost at scale, and commercial safety to guide build-versus-buy decisions.
  • Encourage a collaborative environment where data scientists, designers, and engineers can test ideas quickly, learn from setbacks, and deliver with confidence.
  • Convert AI capabilities and business needs into intuitive visual workflows that support creative and production users while reducing friction.
  • Create detailed business requirements and user stories to guide cross-functional teams through complex AI-driven visual product work.
  • Identify risks, technical limitations, and capability gaps early, and help the team address them before they create delivery issues.

Requirements

  • At least 3 years of experience building and launching digital products with designers, engineers, and data scientists.
  • Practical experience using generative AI tools, image generation and editing tools, agentic workflows, or similar visual AI applications.
  • Ability to work with data science teams, convert model capabilities into usable product requirements, and explain technical tradeoffs to non-technical audiences.
  • Strong communication and storytelling skills, with the confidence to work through ambiguity and present a clear point of view to stakeholders at different levels.
  • Experience reviewing and choosing AI/ML tools or vendors by evaluating output quality, integration fit, cost at scale, and readiness for production.
  • Comfort in fast-changing, uncertain environments where structure needs to be created rather than inherited.
  • Genuine interest in innovation, generative AI, and the opportunity to shape the product lifecycle.
  • Experience in fashion, retail, or consumer product settings is an advantage.

Additional information

This is a full-time, on-site role based in Philadelphia, Pennsylvania. The posting does not specify salary, benefits, education, eligibility restrictions, openings, or start date. No internship duration applies.

Ideal fit

The role suits someone who can bridge creative, technical, and commercial priorities, especially in a fast-moving AI environment where experimentation, structure, and delivery all matter equally.

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