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AppZen, Inc.
San Jose, California
Source: AppZen, Inc. careers · View original posting
From AppZen, Inc.'s posting. “We” and “our” refer to the employer.
AppZen is the leader in autonomous spend-to-pay software. Its patented artificial intelligence accurately and efficiently processes information from thousands of data sources so that organizations can better understand enterprise spend at scale to make smarter business decisions. It seamlessly integrates with existing accounts payable, expense, and card workflows to read, understand, and make real-time decisions based on your unique spend profile, leading to faster processing times and fewer instances of fraud or wasteful spend.
Global enterprises, including one-third of the Fortune 500, use AppZen’s invoice, expense, and card transaction solutions to replace manual finance processes and accelerate the speed and agility of their businesses.
At AppZen, we value candidates who are actively using AI tools to enhance productivity, automate repetitive tasks, and solve problems more efficiently. Across all roles, we are looking for team members who leverage AI in meaningful ways to drive impact in their work.
To learn more, visit us at www.appzen.com.
As a Senior Product Designer at AppZen, you'll shape the user experience for our products from planning to delivery. You will collaborate with cross-functional teams and Fortune 500 clients to design workflows and interactions that set new industry standards. This role offers a unique chance to create innovative solutions that have never been seen before in the industry, helping to shape the future of how companies manage their financial processes.
This role is expected to commute to the San Jose office four days a week on Mondays through Thursdays.
Responsibilities:: Own the end-to-end experience for core products, from planning to launch, partnering with the Principal Designer, Product, and Engineering to find the right problems to solve
Design AI-powered and agentic workflows that finance teams can understand and trust, including explainability, confidence signals, human-in-the-loop review, and graceful handling of model errors
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