UX Conversation Designer, Senior Associate

📍 Job Overview

Job Title: UX Conversation Designer, Senior Associate

Company: JPMorgan Chase & Co.

Location: Brooklyn, NY

Job Type: Full time

Category: User Experience / Conversational AI Design

Date Posted: 2026-01-21T22:24:00

Experience Level: 2-5 Years

Remote Status: On-site

🚀 Role Summary

• This role focuses on designing and developing conversational experiences for internal employee tools, specifically the Employee Assistant, leveraging expertise in Large Language Models (LLMs).

• The position requires a blend of User Experience (UX) Design, Conversational AI Design, and a strong understanding of LLM capabilities to drive innovation in internal product development.

• The Senior Associate will collaborate extensively with cross-functional teams, including Machine Learning (ML) engineers, to integrate and optimize AI-driven solutions within the enterprise.

• Success in this role hinges on translating user insights and business needs into intuitive, user-centric conversational interfaces that enhance employee efficiency and engagement.

📝 Enhancement Note: While the core responsibilities lean heavily into UX and Conversational AI, the emphasis on LLMs and collaboration with ML teams positions this role at the intersection of design and AI development. This suggests a need for candidates who can bridge technical understanding with design execution, a critical skill for modern AI-driven product teams. The "Employee Experience team" context indicates a focus on internal tools and processes, differentiating it from customer-facing roles.

📈 Primary Responsibilities

• Design AI-powered end-to-end use case flows for chat, voice, and multi-modal interfaces for the Employee Assistant, utilizing wireframes, prototypes, decision trees, logic frameworks, and prompt playgrounds.

• Propose intuitive, user-centric solutions that drive efficiency and user engagement, ensuring alignment with overarching business objectives and enterprise strategies.

• Conduct or collaborate with UX Research on usability testing, observational testing, and other research methods to gather actionable data insights from real users.

• Employ an iterative design mindset, actively gathering and incorporating user and agent feedback to continuously enhance the Employee Assistant's overall experience.

• Work within an established Design System to produce and contribute to patterns, including Conversational UI components, and to develop and refine the Visual and Conversational Design Language.

• Leverage expertise in LLMs to contribute to the broader Conversational AI strategy, specifically focusing on how design processes evolve when building with LLMs.

• Conduct data-driven analyses to inform design decisions, transforming raw information into valuable insights for strategic decision-making and process optimization.

• Collaborate effectively with cross-functional teams, including ML engineers and product managers, to integrate UX and Conversational Design principles into the product development lifecycle.

• Support the training of LLMs based on established Conversational Design principles and industry best practices, working closely with ML teams.

• Facilitate ideation and alignment workshops with project stakeholders to ensure shared understanding and buy-in for design initiatives.

• Present design work and rationale clearly and impactfully to business stakeholders and the broader product/technology organization through engaging storytelling and comprehensive documentation.

📝 Enhancement Note: The responsibilities highlight a strong emphasis on the full design lifecycle, from ideation and research to implementation and iteration. The inclusion of "prompt playgrounds" and "agent logic" indicates a hands-on approach to conversational AI development, moving beyond traditional UX deliverables. The requirement to contribute to the "broader Conversational AI strategy" and "how design processes will evolve when building with LLMs" suggests a forward-looking role influencing future design methodologies.

🎓 Skills & Qualifications

Education: Specific educational requirements are not detailed, but a strong portfolio and relevant experience are paramount. A Bachelor's or Master's degree in Design, Human-Computer Interaction, Computer Science, or a related field would be beneficial.

Experience: 3+ years of experience in User Experience Design, Conversational AI Design, or similar roles focused on designing for Large Language Models (LLMs).

Required Skills:

• Demonstrated ability to create 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 various fidelity levels.

• Proven experience deploying Conversational AI solutions (e.g., chatbots, virtual assistants) leveraging natural language processing (NLP) and AI technologies.

• Experience designing user experiences across multiple platforms, including web, mobile, and other digital channels.

• Expertise in creating inclusive designs and ensuring adherence to accessibility guidelines and assistive technologies, incorporating diverse user perspectives.

• Ability to plan and organize design work from initial concept through execution, advocating for and implementing Conversation Design best practices.

• Capacity to manage ambiguity, work autonomously, and multitask effectively within an agile development environment.

• Skill in interpreting complex data and transforming it into actionable insights for informed decision-making and strategic planning.

• Ability to develop innovative experiences that meet or exceed initial product proposals, creating 'north star' representations to drive customer- and employee-centric decision-making.

• Proficiency in designing high-density and data-driven conversational experiences.

• Familiarity with all 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.

Preferred Skills:

• Experience designing and deploying experiences using prompt playgrounds such as MindStudio or similar platforms.

• Prior experience supporting design work in employee assistant tools, Conversational AI, or AI-driven product teams.

• Experience working in complex business domains or enterprise environments (e.g., financial services) 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, AI model deployment).

• Understanding of product lifecycles from a UX and conversational AI perspective, including how user and conversational experiences evolve throughout different stages.

📝 Enhancement Note: The required skills list is robust, emphasizing practical design execution with conversational AI tools, research integration, and cross-functional collaboration. The preference for experience with specific prompt playground tools and within enterprise/financial services contexts provides clear direction for candidates. The distinction between "required" and "preferred" skills helps candidates prioritize their application focus.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies: Detailed case studies showcasing end-to-end design projects for conversational interfaces (chatbots, virtual assistants, voice interfaces). Each case study should clearly articulate the problem, your role, the design process, key decisions, and measurable outcomes.

• Process Documentation: Evidence of your structured approach to design, including research findings, user journey maps, wireframes, flow diagrams, prototypes, and final design specifications for conversational elements.

• LLM Integration Examples: If possible, highlight projects where you considered or incorporated Large Language Models, demonstrating understanding of their potential and limitations in design.

• Tool Proficiency: Showcase examples of work created using common conversation design platforms (e.g., Dialogflow, VoiceFlow, Microsoft Bot Framework, MindStudio) or prototyping tools relevant to conversational design.

• Impact Metrics: Quantify the impact of your design solutions where possible (e.g., improved task completion rates, reduced support tickets, increased user satisfaction, efficiency gains).

Process Documentation:

• Workflow Design: Demonstrate ability to map out and optimize complex user workflows for conversational systems, including decision trees and logic frameworks.

• Iterative Design: Provide examples of how you've incorporated user feedback and data analytics into iterative design improvements for conversational agents.

• System Integration: Illustrate understanding of how conversational interfaces integrate with backend systems, APIs, and data sources to deliver a seamless user experience.

• Design System Contribution: Show examples of contributions to or utilization of design systems, particularly for conversational UI components or visual/conversational design languages.

📝 Enhancement Note: For a role focused on Conversational AI and LLMs, the portfolio must go beyond traditional UX deliverables. Candidates should emphasize their ability to design complex conversational flows, understand the technical underpinnings of AI, and demonstrate iterative improvement based on data and user feedback. Highlighting experience with LLM-specific design considerations and relevant tools will be critical.

💵 Compensation & Benefits

Salary Range: For a Senior Associate UX Conversation Designer in Brooklyn, NY, with 3-5 years of experience at a major financial institution like JPMorgan Chase, the estimated salary range is $100,000 - $140,000 per year.

Benefits:

• Comprehensive health care coverage (medical, dental, vision).

• On-site health and wellness centers.

• Retirement Savings Plan (e.g., 401(k) with company match).

• Backup childcare services.

• Tuition reimbursement for continued education and professional development.

• Mental health support programs and resources.

• Financial coaching and planning services.

• Potential for discretionary incentive compensation based on performance.

Working Hours: Standard full-time hours, likely around 40 hours per week. While the role is on-site, there may be flexibility in daily start/end times, subject to team and business needs. Adherence to project deadlines may occasionally require extended hours.

📝 Enhancement Note: Salary is estimated based on industry benchmarks for UX/Conversational AI Designers in the New York City metropolitan area, factoring in the Senior Associate level, the specific skills requested (LLMs, Conversational AI), and the employer's status as a large financial institution. The provided benefits are directly from the job description and are standard for large corporations.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services / Banking. JPMorgan Chase is one of the world's largest and most established financial institutions, operating across investment banking, consumer banking, commercial banking, and asset management.

Company Size: Large Enterprise (over 10,000 employees). This means established processes, a wide range of specialized teams, and significant resources for development and innovation.

Founded: Over 200 years ago. This extensive history signifies stability, deep industry knowledge, and a long-term strategic outlook.

Team Structure:

• Employee Experience Team: This role is part of the Employee Experience team within Human Resources. This team focuses on shaping the firm's culture, developing a diverse and inclusive workforce, and enhancing the internal employee journey.

• Cross-functional Collaboration: The UX Conversation Designer will work closely with Product Managers, ML Engineers, UX Researchers, other Designers, and business stakeholders across various departments.

• Reporting Structure: Likely reports to a Design Lead or Manager within the Employee Experience or HR Technology group, with direct collaboration across multiple project teams.

Methodology:

• User-Centered Design & Design Thinking: The team emphasizes understanding user needs to drive product development and strategic initiatives.

• Agile Development: Projects are likely managed using agile methodologies, requiring iterative design, continuous feedback, and adaptability.

• Data-Driven Decision Making: Insights from data analysis and user research are crucial for informing design choices and measuring impact.

• AI Integration: A strategic focus on leveraging AI, particularly LLMs, to improve internal tools and processes.

Company Website: https://www.jpmorganchase.com/

📝 Enhancement Note: The context of JPMorgan Chase as a large, established financial institution implies a structured, process-driven environment with a strong emphasis on compliance, security, and scale. The "Employee Experience team" focus within HR highlights a strategic investment in internal tools and employee well-being, driven by technology and design.

📈 Career & Growth Analysis

Operations Career Level: Senior Associate. This level typically signifies an individual contributor role with significant responsibility and a need for autonomy. It implies the ability to lead design initiatives, mentor junior designers (though not explicitly stated), and contribute to strategic discussions.

Reporting Structure: The role reports into the Employee Experience team, likely within Human Resources or HR Technology. This means direct collaboration with HR functions, IT, and potentially business units that utilize the Employee Assistant. The reporting line will likely be to a Design Manager or Lead, who in turn reports to higher levels of HR/Technology leadership.

Operations Impact: The primary impact of this role is on improving internal employee efficiency, engagement, and satisfaction through enhanced digital tools. By designing effective conversational interfaces for the Employee Assistant, the role directly contributes to streamlining HR processes, knowledge access, and task completion for all employees, thereby indirectly supporting broader business objectives by improving workforce productivity and experience. The focus on LLMs also positions this role to influence the company's broader strategy for AI adoption within its operations.

Growth Opportunities:

• Specialization: Deepen expertise in Conversational AI, LLM design, and specific enterprise applications within financial services.

• Leadership: Progress to Lead UX Conversation Designer, Design Manager, or Product Owner roles, leading teams and strategic initiatives.

• Cross-functional Mobility: Transition into related roles within product management, UX research, or AI strategy within the company.

• Skill Development: Opportunities for training in advanced AI technologies, design leadership, and complex enterprise systems.

📝 Enhancement Note: The "Senior Associate" title suggests a mid-level to senior individual contributor role, with expectations of independent work and strategic input. The emphasis on LLMs and internal tools points to a growth area within large enterprises, offering significant opportunities for specialization and impact.

🌐 Work Environment

Office Type: The role is explicitly listed as "On-site," with a specific address at 4 Chase Metrotech Center in Brooklyn, NY. This indicates a corporate office environment typical of a large financial institution.

Office Location(s): 4 Chase Metrotech Center, Brooklyn, NY 11245. This is a significant office building in a commercial hub within Brooklyn, likely offering good access to public transportation.

Workspace Context:

• Collaborative Spaces: Expect a modern office setup with dedicated areas for individual work and collaborative spaces for team meetings, workshops, and brainstorming sessions.

• Technology Access: Access to high-performance workstations, design software, and all necessary tools for UX and Conversational AI design.

• Team Interaction: Frequent opportunities for face-to-face interaction with colleagues within the Employee Experience team, cross-functional partners, and potentially other design professionals across the firm.

Work Schedule: Standard full-time hours (approximately 40 hours/week) are expected, with an on-site presence required. While the core hours will be defined, the agile nature of project work may necessitate some flexibility.

📝 Enhancement Note: The on-site requirement at a specific corporate address in Brooklyn suggests a traditional office-based work environment. This often implies a structured schedule and direct, in-person collaboration, which can be beneficial for complex design discussions and team cohesion within a large organization.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will likely review applications and resumes to assess basic qualifications and fit.

• Portfolio Review & Technical Interview: Candidates will be asked to present their portfolio, showcasing relevant UX and Conversational AI design projects. This will be followed by in-depth technical questions about design process, LLM understanding, tool proficiency, and problem-solving approaches.

• Design Challenge/Case Study: A practical exercise may be given, requiring candidates to design a conversational flow or solve a specific user problem related to the Employee Assistant or a similar scenario.

• Behavioral & Cultural Fit Interviews: Interviews with team members and hiring managers to assess collaboration skills, communication style, ability to manage ambiguity, and alignment with JPMorgan Chase's values and the team's culture.

• Final Interview: Potentially with senior leadership for final approval.

Portfolio Review Tips:

• Focus on Conversational AI: Prioritize case studies that demonstrate your expertise in designing conversational interfaces, including logic, flows, and user journeys for chatbots or virtual assistants.

• Highlight LLM Understanding: If possible, include projects that show your consideration of LLMs, prompt engineering basics, or how you've adapted designs for AI-driven interactions.

• Showcase Process: Clearly articulate your design process, from research and ideation to prototyping and iteration. Explain your decision-making rationale at each step.

• Quantify Impact: Whenever possible, use metrics to demonstrate the success of your designs (e.g., improved task completion, user satisfaction scores, efficiency gains).

• Tailor Your Presentation: Be prepared to speak specifically about how your skills and experience can benefit JPMorgan Chase's Employee Experience team and the Employee Assistant product.

Challenge Preparation:

• Understand the Context: Research JPMorgan Chase, its mission, and the likely needs of its employees. Think about common internal support or information access challenges.

• Practice Conversational Flow Design: Be ready to sketch out user flows, decision trees, and dialogue examples for common scenarios (e.g., HR policy questions, IT support requests, onboarding tasks).

• Consider LLM Integration: Think about how LLMs could enhance the proposed solution, including potential benefits and limitations.

• Communicate Your Thinking: Clearly articulate your assumptions, design choices, and the reasoning behind them during the challenge presentation.

📝 Enhancement Note: The interview process is expected to be rigorous, with a strong emphasis on a candidate's portfolio and practical design skills, particularly concerning conversational AI and LLMs. Candidates should prepare to demonstrate not just design execution but also strategic thinking and an understanding of enterprise environments.

🛠 Tools & Technology Stack

Primary Tools:

• Conversation Design Platforms: Experience with tools like MindStudio, Dialogflow, VoiceFlow, Microsoft Bot Framework, or similar platforms for designing, prototyping, and potentially deploying conversational interfaces.

• Prototyping Tools: Proficiency in standard UX prototyping tools such as Figma, Sketch, Adobe XD, or specialized conversational prototyping tools.

• Wireframing Tools: Tools like Balsamiq, Axure RP, or general design suites for creating visual representations of user journeys and interfaces.

Analytics & Reporting:

• Data Analysis Tools: Familiarity with tools for analyzing user behavior, conversation logs, and performance metrics. This could include SQL, Python for data analysis, or specific analytics platforms.

• Dashboarding Tools: Experience with platforms like Tableau, Power BI, or internal reporting tools to visualize data and track key performance indicators (KPIs) for conversational agents.

CRM & Automation:

• Internal Systems: While not explicitly mentioned, experience with enterprise-level internal platforms or CRM-like systems that manage employee data and interactions would be beneficial.

• AI/ML Platforms: Familiarity with the concepts and workflows associated with Machine Learning platforms, especially those related to Natural Language Processing (NLP) and Large Language Models (LLMs), is a plus.

📝 Enhancement Note: The core requirement is proficiency in conversation design platforms. Beyond that, a strong understanding of data analysis for informing design and familiarity with the broader AI/ML ecosystem (especially LLMs) are key. The ability to integrate with existing enterprise systems and leverage design systems will also be crucial.

👥 Team Culture & Values

Operations Values:

• User-Centricity: A deep commitment to understanding and advocating for the employee user, ensuring their needs are at the forefront of all design decisions.

• Innovation: Driving forward with new technologies and methodologies, particularly in the AI and Conversational AI space, to create cutting-edge employee experiences.

• Collaboration: Fostering a team environment where cross-functional partners work together seamlessly, sharing knowledge and driving collective success.

• Data-Driven: Utilizing data and insights from research and analytics to inform design strategies and measure the impact of solutions.

• Efficiency & Impact: Focusing on designing solutions that not only improve the user experience but also drive tangible business outcomes and operational efficiency.

Collaboration Style:

• Cross-functional Integration: Actively engaging with product managers, engineers (ML/software), researchers, and business stakeholders to ensure design solutions are technically feasible, strategically aligned, and meet business objectives.

• Open Communication: Encouraging clear, honest, and constructive feedback exchange within the team and with stakeholders to refine designs and processes.

• Workshop Facilitation: Leading and participating in design-led workshops to foster alignment, generate ideas, and build consensus among diverse groups.

• Knowledge Sharing: Contributing to the team's collective knowledge base by documenting best practices, sharing learnings, and mentoring where appropriate.

📝 Enhancement Note: The values emphasize a proactive, user-focused, and data-informed approach to design within a corporate, collaborative setting. The focus on AI and efficiency suggests an environment that encourages continuous improvement and technological adoption.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Innovation with Enterprise Constraints: Integrating cutting-edge AI technologies (LLMs) within a large, regulated financial institution requires navigating complex security, compliance, and legacy system challenges.

• Designing for Diverse Employee Needs: Creating a universally effective Employee Assistant that caters to a wide range of employee roles, technical proficiencies, and needs across a global organization.

• Evolving LLM Landscape: Staying abreast of rapid advancements in LLM technology and adapting design strategies and tools accordingly, while managing expectations and potential limitations.

• Measuring ROI of Conversational AI: Quantifying the business value and return on investment for conversational AI initiatives, especially for internal tools, can be complex.

Learning & Development Opportunities:

• Advanced AI/LLM Training: Access to specialized courses, workshops, and resources to deepen understanding and application of LLMs and conversational AI technologies.

• Enterprise Design Systems: Opportunities to contribute to and learn from sophisticated enterprise-level design systems and their application to complex products.

• Cross-Disciplinary Exposure: Working closely with ML engineers, data scientists, and product strategists provides exposure to different technical and business domains.

• Leadership Development: Potential for growth into leadership roles, managing projects, teams, and strategic design initiatives within the Employee Experience domain.

📝 Enhancement Note: The challenges presented are typical for roles at the intersection of cutting-edge technology and large, established enterprises. The growth opportunities are strong, particularly for those looking to specialize in AI-driven design within a stable, resource-rich environment.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex conversational flow you designed. What were the key decision points, and how did you ensure user-friendliness and efficiency?" (Focus on process, decision-making, and user-centricity.)

• "How do you approach designing for Large Language Models? What are the unique considerations compared to traditional rule-based chatbots, and how do you mitigate potential issues like hallucinations or bias?" (Demonstrate LLM understanding and risk mitigation.)

Company & Culture Questions:

• "Why are you interested in designing for employee experience at a financial institution like JPMorgan Chase?" (Show understanding of the company's context and employee focus.)

• "How do you collaborate with technical teams, such as ML engineers, to bring conversational AI designs to life?" (Assess cross-functional collaboration skills and technical fluency.)

Portfolio Presentation Strategy:

• Storytelling Approach: Frame each case study as a narrative: the challenge, your role and approach, the solutions you designed, and the outcomes achieved.

• Visual Clarity: Ensure your slides are clean, visually appealing, and effectively communicate the user flows, interface designs, and key data points.

• Focus on LLM Relevance: If applicable, highlight any projects where you considered or integrated LLMs, explaining your thought process regarding their capabilities and limitations.

• Prepare for Deep Dives: Be ready to answer detailed questions about your design decisions, research methodologies, and the tools you used.

• Highlight Iteration: Show how you incorporated feedback and data to refine designs, demonstrating an iterative and user-focused approach.

📝 Enhancement Note: Interview preparation should focus on showcasing practical design skills, a strong understanding of AI/LLMs, and the ability to operate within a large enterprise context. Candidates must be ready to articulate their process, defend their design choices, and demonstrate how they drive measurable impact.

📌 Application Steps

To apply for this UX Conversation Designer position:

• Submit your application through the provided Oracle Cloud portal link.

• Portfolio Customization: Ensure your portfolio prominently features case studies related to conversational AI, chatbots, virtual assistants, and ideally, any experience with LLM-driven applications or prompt engineering. Tailor your presentation to highlight your understanding of user journeys and complex conversational flows.

• Resume Optimization: Update your resume to clearly articulate your years of experience in UX and Conversational AI Design, specifically mentioning proficiency with relevant tools (Dialogflow, VoiceFlow, MindStudio, etc.) and your experience with LLMs, NLP, and user research. Quantify achievements where possible.

• Interview Practice: Prepare to discuss your design process, how you handle ambiguity, your approach to inclusive design, and your collaboration style. Practice articulating your rationale for design decisions and be ready to present your portfolio effectively. Research JPMorgan Chase's mission and values.

• Company Research: Understand JPMorgan Chase's position in the financial services industry and its commitment to employee experience and technological innovation. Familiarize yourself with their stated values and how they might apply to a role focused on internal tools and AI.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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