UX Researcher, Principal

About Blackbaud / UX Team

Blackbaud is the world’s leading provider of AI-powered solutions for social impact, supporting nonprofits, K-12 schools, higher education, arts and cultural organizations, healthcare, corporate impact teams, and individual changemakers with solutions for giving, connecting, and engaging. Our work helps mission-driven organizations better understand their communities, strengthen relationships, and move resources where they are needed most.

As part of the UX team, you will help shape thoughtful, trustworthy, and human-centered product experiences for a wide range of users, including enterprise nonprofits, small charities, individual fundraisers, and donors. You will work closely with product, design, engineering, analytics, and UX leadership to uncover user needs, guide product strategy, and ensure our AI-powered experiences are useful, responsible, and easy to trust.

Job Summary

We are looking for a Principal UX Researcher to lead strategic research that builds a deep understanding of how people engage with Blackbaud’s products, especially as AI becomes more embedded in their day-to-day workflows.

In this role, you will identify high-impact research opportunities, lead complex research across a capability or solution area, and help teams understand not only what users need, but how they think, decide, trust, and respond when working with intelligent systems. You will play a key role in shaping AI-assisted experiences that feel transparent, reliable, and genuinely helpful.

This role is ideal for someone who is self-directed, strong in both qualitative and quantitative research, comfortable with ambiguity, and passionate about mentoring others while raising the quality and impact of research across teams.

Key Responsibilities

• Identify research opportunities and lead strategic research within a product capability or solution area.

• Plan and execute research using the right mix of qualitative, quantitative, generative, and evaluative methods to answer complex and longer-term questions.

• Study human-AI interaction, including how users interpret, trust, rely on, recover from, and respond to AI outputs.