Ux Conversation Designer, Vice President

JPMorgan Chase JPMorgan Chase · Banking · Brooklyn, NY +1 · Corporate Sector

This role focuses on designing the conversational experience for an internal Employee Assistant, leveraging large language models (LLMs) and AI technologies. The UX Conversation Designer will create AI-powered use case flows, conduct user research, and collaborate with ML teams to train LLMs, ultimately shaping the user experience of AI-driven internal products.

What you'd actually do

  1. Design AI-powered end-to-end use case flows (for chat interfaces, voice interfaces, and multi-modal experiences) for the Employee Assistant through wireframes, prototypes, decision trees, logic frameworks, prompt playgrounds, or other Conversational AI tools
  2. Propose solutions that are intuitive, user-centric, drive efficiency and user engagement while also aligning with business objectives
  3. Conduct or work with UX Research to conduct usability testing, observational testing, and other forms of research to gather data insights from real users
  4. Operate with an iterative design mindset, gathering and incorporating user and agent feedback to continuously improve the overall experience the Employee Assistant
  5. Leverage expertise in LLMs to contribute to the broader Conversational AI strategy, including how design processes will evolve when building with LLMs

Skills

Required

  • 4+ years of experience or equivalent expertise in User Experience Design, Conversational AI Design, or similar roles designing for LLMs
  • Demonstrate ability to visual representations of user journeys, storyboarding, wireframes, prototypes, agent logic, agent decision points, and conversational flows using conversation design platforms (e.g., MindStudio, Dialogflow, VoiceFlow, Microsoft Bot Framework, or similar) at different levels of fidelity
  • Experience deploying Conversational AI solutions (e.g., chatbots, virtual assistants) using natural language processing and AI technologies.
  • Demonstrated experience designing across multiple platforms, including web, mobile, and other digital channels
  • Experience creating inclusive designs, accessibility guidelines, and assistive technologies that incorporate diverse perspectives
  • Ability to plan and organize design work from initial concept through execution and advocate for Conversation Design best practices.
  • Ability to manage ambiguity, work autonomously, and multi-task in an agile environment and experience interpreting complex data and transforming it into actionable insights for informed decision-making
  • Ability to develop experiences that meet or exceed the initial proposal of a product or experience, including the development of innovation strategies and the creation of 'north star' representations to drive customer-centric and employee-centric decision-making.
  • Proficiency designing high-density and data-driven conversational experiences.
  • Familiar with the different phases of the user research and design process—including validating hypotheses with users, effectively communicating concepts, and creating low/high fidelity prototypes for both visual and conversational interfaces.

Nice to have

  • Experience designing and deploying experiences using prompt playgrounds such as MindStudio or similar
  • Experience supporting design work in employee assistant tools, Conversational AI, or AI-driven product teams.
  • Prior experience working in complex business domains or in enterprise environments (financial services or other) working on large-scale transformation programs, including AI tool deployment.
  • Ability to understand and articulate how technical constraints and opportunities—including AI/ML capabilities—influence design solutions.
  • Familiarity with technology concepts and an understanding of various technical approaches and lifecycles (e.g., agile development methodologies, DevOps practices, frontend development structures, and AI model deployment).
  • Understanding of product lifecycles from a UX and conversational AI perspective (e.g., how user and conversational experiences evolve throughout the different stages of a product's lifecycle)

What the JD emphasized

  • Conversational AI design
  • large language models (LLMs)
  • designing for LLMs
  • AI-powered end-to-end use case flows
  • Conversational AI tools
  • Conversational AI strategy
  • train LLMs

Other signals

  • designing conversational AI for internal employee assistant
  • leveraging LLMs to inform strategy
  • designing AI-powered end-to-end use case flows