Job description

URBN is hiring a Staff Engineer (GenAI) to join the development of AI-powered visual experiences, with a primary focus on building and operationalizing image and video generation systems. We are looking for an experienced engineer to join our mission of integrating generative AI solutions with creative tools and production workflows. In this role, you will own the engineering side of multi-model generative pipelines, turning research prototypes into reliable, scalable services that power AI-first innovations across our digital ecosystem. You will collaborate with a talented cross-functional team comprising data scientists, UX designers, product managers, creative partners, and domain experts to deliver significant business impact. This role will focus on making generative systems robust, efficient, and production-ready. The ideal candidate brings deep software engineering fundamentals, comfort with agentic AI tooling, and enough generative AI fluency to wrangle prompts, orchestrate multi-step visual workflows, and reason about output quality, even if they are not the one doing final model tuning or evaluation design. If you are energized by the intersection of software engineering and generative AI, and you want to build the infrastructure and tooling that turns cutting-edge image and video models into real products, we invite you to help shape the future of intelligent, AI-native creative experiences at URBN. • Design, build, and optimize image and video generation pipelines (generation, inpainting, upscaling, style transfer, conditioning, post-processing) into production-ready, observable services with attention to cost, latency, and throughput. • Design and develop agentic workflows (ADK, A2A, LangGraph, or similar), MCP servers (FastMCP or similar), and microservices (FastAPI, GraphQL, or similar) to orchestrate and serve generative AI capabilities at scale. • Develop prompt management systems and structured prompting strategies for consistent visual output, learning on the job how to wrangle prompts for fashion-specific and virtual try-on use cases. Engineer consistency mechanisms and quality gates in partnership with data scientists who own evaluation methodology. • Integrate multimodal and vision-language models into production workflows for image understanding, automated tagging, captioning, and quality pre-screening. • Collaborate with Product Designers, Product Managers, Data Scientists, and other Engineers to translate brand and business needs into scalable generative AI solutions. Evaluate new technologies, models, and vendors through proof-of-concept studies. • Implement and maintain ML architecture, including pipelines and applications that enable training and inference of generative models in production. Champion best practices in full-stack algorithm engineering. • Generative AI Systems: 1+ year of hands-on experience building or operationalizing image generation systems (diffusion models, multimodal pipelines) in a professional applied context. Working familiarity with the rapidly evolving landscape of image and video generation models and orchestration patterns. • AI-Augmented Development & Agentic AI: Proficient with AI-powered development tools (e.g., Cursor, VS Code Copilot, Claude Code, or Gemini). Experience designing agentic workflows or AI orchestration systems using LangGraph, ADK, A2A, CrewAI, or similar. Familiarity with MCP (Model Context Protocol) is a strong plus. • Python & ML Frameworks: Strong proficiency in Python, with practical experience using PyTorch and/or Hugging Face for model serving, fine-tuning support, and inference optimization. • APIs, Distributed Systems & Cloud: Strong background in scalable RESTful APIs, microservices architecture, and high-availability distributed systems. Proficiency with Docker, container orchestration, cloud-native services, and cloud-based AI infrastructure. Experience with Terraform or similar IaC tooling. • Engineering Practices: Dedication to CI/CD pipelines, TDD, and automated code quality standards. Excellent communicator who can bridge technical, data science, and creative teams. Comfortable with ambiguity and minimal oversight. • Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field, or equivalent practical experience. Nice to Haves • Experience with video generation models, or with fashion/retail/e-commerce applications of generative AI such as virtual try-on, AI product photography, or on-model image generation. • Experience building tooling and orchestration for model fine-tuning workflows (LoRA, DreamBooth, ControlNet, IP-Adapter, textual inversion), enabling data scientists to iterate quickly on adaptation techniques. • Background in computer vision fundamentals (segmentation, detection, embeddings) or LLM evaluation frameworks for generative outputs. • Experience with prompt engineering at scale, creative design tools (Adobe Photoshop, Firefly, Figma), or data pipeline orchestration (Airflow, dbt, or similar). URBN offers comprehensive Perks & Benefits to employees. Availability and eligibility to specific benefits may be subject to your location and employment status. Benefits include medical, dental, vision, PTO, generous employee discounts, retirement savings and much more! For additional information visit www.urbn.com/work-with-us/benefits URBN celebrates diversity and is committed to creating an inclusive environment for all employees. We are proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, sex (including gender, pregnancy, sexual orientation, and gender identity or expression), religion, creed, age, physical or mental disability, national origin or ancestry, ethnicity, citizenship, service in the uniformed services, genetic information, or any other protected characteristic as established by law. We believe strongly in fostering a safe, fair and respectful work environment. To ensure compliance with our non-discrimination and anti-harassment policies, we offer anti-harassment training to managers and employees.

Requirements

Must-haves

Design and develop agentic workflows (ADK, A2A, LangGraph, or similar), MCP servers (FastMCP or similar), and microservices (FastAPI, GraphQL, or similar) to orchestrate and serve generative AI capabilities at scale.
Integrate multimodal and vision-language models into production workflows for image understanding, automated tagging, captioning, and quality pre-screening.
Implement and maintain ML architecture, including pipelines and applications that enable training and inference of generative models in production. Champion best practices in full-stack algorithm engineering.
Python & ML Frameworks: Strong proficiency in Python, with practical experience using PyTorch and/or Hugging Face for model serving, fine-tuning support, and inference optimization.
Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field, or equivalent practical experience.

Nice-to-haves

Experience with video generation models, or with fashion/retail/e-commerce applications of generative AI such as virtual try-on, AI product photography, or on-model image generation.
Experience building tooling and orchestration for model fine-tuning workflows (LoRA, DreamBooth, ControlNet, IP-Adapter, textual inversion), enabling data scientists to iterate quickly on adaptation techniques.
Background in computer vision fundamentals (segmentation, detection, embeddings) or LLM evaluation frameworks for generative outputs.
Experience with prompt engineering at scale, creative design tools (Adobe Photoshop, Firefly, Figma), or data pipeline orchestration (Airflow, dbt, or similar).

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigraphqlmlpythondockerci/cdllmfigma

Platform: icims
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

Pto