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Job Description: UX Researcher, AI & LLM Products (Contract)

Team: Foundation Model Group, Prescient Design (AI for Drug Discovery)

Location: New York, NY (Manhattan) - Local candidates strongly preferred.

The Foundation Model group within Prescient Design is seeking an exceptional UX Researcher for a 6-month contract. Our team is at the forefront of developing AI and agentic frameworks to revolutionize drug discovery. We are specifically looking for candidates with direct experience in LLMs (Large Language Models) and AI agents, and/or a background in biotech, pharma, or a related industry, with a proven track record of shipping internal software products.
As the bridge between our AI development team and our users—world-class scientists and biomedical experts—your mission is to ensure our agentic framework is not only powerful but also intuitive and seamlessly integrated into the complex workflows of cutting-edge drug discovery. You will champion a user-centered approach, translating deep user insights into a product that accelerates scientific breakthroughs.

The Hiring Manager is prioritizing profiles with experience in LLMs/agents and a background in biotech, pharma, or a related field, specifically those who have shipped an internal build, software, or product.

The Role

In this role, you will be instrumental in shaping the user experience of our internal AI platforms. Your key responsibilities will include:

Define AI Product Strategy Through UX Research: Lead end-to-end user research to directly inform the product roadmap for our agents and LLM-based applications. Identify critical pain points in scientific workflows and uncover new opportunities for AI to drive efficiency and discovery.
Design and Execute Rigorous Usability Studies for AI Products: Develop and implement specialized user testing methodologies (e.g., contextual inquiries, task-based usability tests) to evaluate the effectiveness and intuitiveness of our LLM-driven interfaces and agentic workflows.
Operationalize User Feedback for AI Systems: Build and manage a systematic process for gathering, analyzing, and tracking qualitative feedback on our models and agents, enabling data-informed improvements to the core AI infrastructure.
Uncover Actionable Insights for Agentic Frameworks: Analyze qualitative data from user sessions to understand how scientists interact with and trust AI outputs. Synthesize findings to reveal what drives user adoption and engagement with complex AI tools.
Build a User-Testing Infrastructure for Internal AI Tools: Create and maintain reusable testing protocols and recruitment pipelines tailored for internal, expert users, elevating the quality and efficiency of user research across the organization.
Collaborate Deeply with AI/ML Engineers & Scientists: Work closely with technical teams to translate complex user needs from drug discovery units into clear, actionable product requirements for our AI models and agentic systems.
Communicate with Clarity and Impact: Synthesize diverse data to provide compelling insights and recommendations. Effectively advocate for the user to both technical and non-technical stakeholders, influencing product features and the strategic roadmap.

Qualifications

3-5+ years of experience conducting UX research and usability testing, preferably with complex, expert-facing systems or internal tools.
3-5+ years of experience in qualitative and quantitative research methods, including generative and usability studies, data analysis, and A/B testing.
Demonstrated experience with AI products, specifically Large Language Models (LLMs) and AI agents.
Experience with UserTesting, Contentsquare, or similar usability testing platforms.
Have experience building and scaling a user research practice, including establishing processes for recruitment, testing, and knowledge management.
Know how to connect deep user insights to product strategy, roadmap decisions, and business impact.
Possess strong analytical skills and are comfortable synthesizing complex, often ambiguous, qualitative data into clear, actionable themes.
Enjoy tackling ambiguous, high-stakes problems and have a genuine curiosity for understanding complex domains like drug discovery.
Communicate with clarity, empathy, and a strategic focus.

Highly Preferred

Direct experience shipping internal software, tools, or products within biotech, pharma, or a related industry.
Hands-on experience with LLM-based applications and standardized protocols like ClientP (Model Context Protocol).
Experience working directly with subject matter experts and stakeholders on internal tools.

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