Principal User Researcher, AI

Autodesk•San Francisco, CA

1d•Hybrid

About The Position

Autodesk is exploring ways to help customers work more effectively across complex design and make workflows, including how agentic capabilities can better connect user intent to outcomes. Reporting to the Sr. Manager, AI User Research, the Principal User Researcher will define and lead research strategy for emerging customer experiences that incorporate agentic capabilities into Autodesk workflows and platforms. This role operates at the intersection of research, product, design, engineering, and AI evaluation—ensuring customer insight meaningfully shapes how new experiences are researched, prototyped, evaluated, and evolved over time. This role will help establish a modern approach to user research for adaptive, AI-enabled systems by integrating qualitative insight, behavioral analysis, experimentation, and continuous feedback mechanisms into product development. The ideal candidate brings deep expertise in human-centered research, systems thinking, and ambiguity navigation, with the ability to influence both near-term product decisions and long-term strategic direction. You will operate with a high degree of autonomy in ambiguous and evolving problem spaces. Success requires not only excellence in research craft, but the ability to define new practices, influence system-level decisions, and connect customer insight directly to product and business outcomes. The Principal User Researcher will play a key role in helping Autodesk design experiences that are intelligent, reliable, trustworthy, and grounded in real customer needs.

Requirements

8+ years of experience in user research, human-computer interaction, cognitive science, or a related field, with a demonstrated track record of driving product impact
Proven ability to define and lead research strategy in complex, ambiguous domains—particularly within AI-enabled, data-driven, or systems-oriented products
Deep expertise in mixed-methods research, including qualitative, quantitative, and behavioral data analysis
Experience designing and operationalizing research frameworks that influence product direction and decision-making at scale
Strong understanding of human-AI interaction, trust, decision-making, and/or cognitive systems
Experience working cross-functionally with Product, Engineering, Design, and Data Science teams
Demonstrated ability to translate research insights into meaningful product, system, or business outcomes
Excellent communication, storytelling, and stakeholder influence skills
Ability to thrive in fast-evolving environments focused on experimentation, prototyping, and discovery

Responsibilities

Define and lead end-to-end research strategy for emerging AI-enabled and agentic customer experiences
Establish research as a core input into product, evaluation, and system design decisions—not solely downstream validation
Translate customer cognition, trust, behavior, and workflow patterns into actionable signals that inform roadmap and experience optimization
Help shape how Autodesk defines and measures customer value within agentic systems and workflows
Influence long-term product and experience direction through research-backed insights and frameworks
Design and operationalize user-centered evaluation frameworks that extend beyond technical accuracy into trust, ambiguity handling, usability, and cognitive outcomes
Partner with Product, Engineering, and AI/ML teams to align technical performance with customer experience quality
Build and evolve continuous feedback loops that connect real-world usage signals to product iteration
Help define evaluation as an ongoing product capability that supports adaptive, learning-oriented experiences
Ensure evaluation frameworks are scalable, reusable, and aligned with iterative product development cycles
Lead research that uncovers latent customer needs through behavioral data, workflow analysis, and real-world usage patterns
Identify high-impact workflow and automation opportunities across design and make experiences
Design research approaches that support continuous learning and iterative product improvement
Translate insights into product opportunities that reduce friction, improve efficiency, and strengthen customer outcomes
Partner cross-functionally to embed insight generation into product experiences and systems
Define and lead research on trust formation, calibration, and recovery within AI-enabled customer experiences
Identify interaction patterns that drive adoption—or create barriers to adoption—across different customer segments
Develop frameworks and guidance for human-AI collaboration experiences that evolve with users over time
Partner with Product and Design teams to ensure onboarding, interaction design, and system behavior support sustained engagement
Translate trust and adoption research into actionable product principles and measurable success criteria
Lead research initiatives exploring how AI-enabled systems influence customer learning, decision-making, and long-term capability development
Define and operationalize approaches for evaluating skill development and workflow transformation within Design + Make industries
Design and test interaction patterns that support learning, professional growth, and effective decision-making
Ensure product decisions consider accessibility, equitable AI use, and broader workforce impact considerations
Contribute to strategic thinking around the future of AI-enabled workflows and industry evolution
Serve as a strategic partner to Product, Engineering, Data Science, and Design teams in shaping priorities and decisions
Drive alignment across research, product development, experience readiness, and optimization efforts
Elevate research impact through clear and compelling communication with senior and executive stakeholders
Contribute to thought leadership around human-centered AI research and adaptive customer experiences
Mentor and guide researchers while helping scale research quality and organizational influence
Shape how Autodesk approaches research for next-generation customer experiences and agentic capabilities over time