Affirm
Staff Product Designer
Remote US · Staff+
Sponsorship not specified$195k-$255kDetected 8 days ago
RESTData ScienceA/B TestingDesign SystemsResearchLeadershipProblem SolvingAdaptability
About the role
- We are looking for an experienced Staff Product Designer to join us at a critical juncture as we evolve how our users interact with Affirm through agentic solutions.
- We are a collaborative, agile team that continues to strive for greater solutions.
Responsibilities
- Own and drive design AI and agentic initiatives for Affirm's Consumer experience, delivering high-impact, customer-centric solutions that align with business objectives.
- Design intuitive, conversational, and agentic patterns that feel proactive and helpful, moving beyond reactive commerce to anticipation.
- Define the design language for Affirm's future AI-driven interactions, prioritizing trust, clarity, and predictable outcomes for our users.
- Collaborate cross-functionally with product, engineering, data science, marketing, and research to drive innovation and deliver seamless, intuitive experiences.
- Push the envelope-challenge the status quo, think outside the box, and take calculated risks to drive meaningful innovation in financial products.
- Bring exceptional visual and interaction design skills to craft delightful, polished experiences that build trust and confidence.
- Champion a test-and-learn mindset, leveraging experimentation, research, and analytics to continuously refine and optimize user experiences.
- AI/Agentic Design Experience: Proven track record of designing AI-driven, agentic, or conversational user interfaces that deliver real user value.
Requirements
- Proficiency in prototyping non-linear, multi-modal user flows to test and validate complex AI interactions.
- 8+ years of product design experience with significant time dedicated to problem solving complex experiences and shipping new products.
- Advanced Prototyping: Proficiency in prototyping non-linear, multi-modal user flows to test and validate complex AI interactions.
- Human-Centered AI Principles: Strong understanding of HCAI principles, focusing on user trust, transparency, system feedback, and explainability.
Skills
- Pay Grade - N
- Equity Grade - 12
- Employees new to Affirm typically come in at the start of the pay range.
- USA base pay range (CA, WA, NY, NJ, CT) per year: $195,000 - $255,000
- USA base pay range (all other U.S. states) per year: $173,000 - $233,000
- Affirm is proud to be a remote-first company!
- A limited number of roles remain office-based due to the nature of their job responsibilities.
- Some key highlights of our benefits package include:
- Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
- Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
- Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
- ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount
Compensation
- Employees new to Affirm typically come in at the start of the pay range.
Benefits
- In addition, you will help create a unified vision on how AI can transform our consumer touchpoints.
- Embrace agility-iterating quickly, adapting to change, and making data-driven decisions while maintaining a strong vision for the future.
- AI Product Design & Strategic Vision
- Health care coverage
- Affirm covers all premiums for all levels of coverage for you and your dependents
Company info
- Product Design at Affirm drives business success by exceeding user expectations.
- We partner closely with Product, Engineering, and Analytics to translate complex user needs into simple, intuitive, and scalable product experiences.
- We rely on empathy, design craft, and systems thinking to champion the user in every decision, ensuring our products empower people to manage their money with confidence.
This listing is sourced directly from Affirm's careers page and normalized into a canonical job model.