Lead Product Designer (LMTS), AI Products

📍 Job Overview

Job Title: Lead Product Designer (LMTS), AI Products

Company: Qualified (Acquired by Salesforce)

Location: San Francisco, California, United States

Job Type: Full-Time

Category: Product Design, AI & Conversational Experiences

Date Posted: June 1, 2026

Experience Level: 6+ Years (with 2+ years in AI/Conversational Design)

Remote Status: Fully Remote (US & Canada)

🚀 Role Summary

• Lead the end-to-end design of innovative AI products, specifically focusing on the "AI brain" and "conversational presence" of autonomous agents like Piper.

• Define and establish new design patterns for autonomous agents within the enterprise sales domain, leveraging rapid prototyping and direct engineering collaboration.

• Shape the user experience of AI collaborators, emphasizing understanding, trust, and user control over AI behavior, personality, and goals.

• Drive product direction and influence design strategy within a lean, intentional design team, with significant ownership from problem definition to launch.

• Collaborate directly with engineering and ML teams, fostering a culture of shared responsibility and rapid iteration, devoid of traditional handoff processes.

📝 Enhancement Note: While this role is for a Product Designer, its focus on AI, conversational interfaces, and autonomous agents places it at the intersection of Product Design and Revenue Operations/Sales Operations enablement. The AI products designed will directly impact sales processes and efficiency, making operations context highly relevant for candidates. The emphasis on "taste over process" and "prototypes over presentations" suggests a highly agile and results-oriented environment, common in fast-paced tech companies aiming to disrupt traditional GTM strategies.

📈 Primary Responsibilities

• Design user interfaces and interaction models for shaping the personality, goals, and objection handling of AI agents, moving beyond standard settings panels to a "thinking partner" concept.

• Develop the live chat and video experience for AI representatives, focusing on micro-interactions, latency handling, turn-taking, and tone to ensure credibility and user trust.

• Create prototypes using code or AI tools, prioritizing speed and effectiveness over traditional design software, to quickly validate concepts and drive development.

• Translate complex LLM behaviors, including latency, streaming, confidence levels, and failure modes, into honest and effective user experiences.

• Work directly with engineering and machine learning teams to integrate AI capabilities seamlessly into the user interface, ensuring a cohesive and functional product.

• Define and document new design patterns for autonomous agents in enterprise sales, contributing to the establishment of industry best practices.

• Conduct user research and gather feedback to iterate on designs, ensuring alignment with user needs and business objectives.

📝 Enhancement Note: The responsibilities highlight a deep dive into AI-driven sales enablement tools. Candidates will need to understand how these AI agents impact sales workflows, lead qualification, pipeline management, and customer engagement, which are core concerns for Revenue Operations and Sales Operations professionals. The ability to design for "autonomous workflows" and "real-time communication" is crucial for optimizing sales team efficiency and effectiveness.

🎓 Skills & Qualifications

Education:

Experience:

• 6+ years of professional product design experience.

• Minimum of 2 years of direct experience designing AI-powered or conversational user experiences.

Required Skills:

• Product Design Leadership: Ability to lead design initiatives with minimal supervision and define problems as well as solutions.

• AI & Conversational Design Expertise: Deep understanding of LLM behavior (latency, streaming, confidence, failure modes) and the ability to design for these characteristics honestly and effectively.

• Prototyping Proficiency: Fluency in prototyping with code or AI tools, in addition to standard design software like Figma. Speed and agility in prototyping are key.

• Visual & Interaction Craftsmanship: Strong aesthetic sensibility and a mastery of interaction design principles, demonstrating excellent taste.

• AI Tooling Fluency: Ability to leverage AI tools as a core part of the design workflow, not just as an experimental addition.

• Cross-functional Collaboration: Experience working directly with engineering and ML teams, fostering a culture of close partnership and shared ownership.

• Problem Definition: Comfort and skill in defining ambiguous problems alongside developing innovative solutions.

Preferred Skills:

• Voice, Video, or Real-time Communication Design: Experience designing interfaces for live, interactive communication platforms.

• Enterprise Sales/CRM Familiarity: Understanding of enterprise sales cycles, workflows, and Customer Relationship Management (CRM) systems.

• Autonomous Workflow Design: Experience designing and implementing multi-step autonomous processes or agent-based systems.

📝 Enhancement Note: The required skills emphasize a blend of traditional design excellence with cutting-edge AI and conversational interface design. For operations professionals considering this role, highlighting experience with AI tools that automate sales tasks, improve lead qualification, or enhance CRM data quality would be highly beneficial. Familiarity with enterprise sales workflows is directly relevant to how these AI products will be integrated and utilized within Sales Operations.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• AI-Driven Design Case Studies: Showcase projects where you designed AI-powered features or conversational experiences, detailing the problem, your approach, and the impact.

• Code/AI Tool Prototyping Examples: Include examples of prototypes built using code or AI tools, demonstrating your ability to move beyond static mocks.

• LLM Behavior Design: Present examples of how you've addressed LLM-specific challenges like latency, streaming output, or confidence levels in your designs.

• Cross-functional Collaboration Evidence: Illustrate instances of close collaboration with engineering and ML teams, highlighting shared problem-solving and integration efforts.

• Problem Definition & Solution Craft: Demonstrate instances where you defined ambiguous problems and developed innovative design solutions.

Process Documentation:

• Evidence of defining and establishing new design patterns for emerging technologies like autonomous AI agents.

• Examples of iterative design processes, including rapid prototyping, user feedback integration, and direct iteration with development teams.

• Documentation or case studies illustrating how you've designed for trust and understanding in AI interactions.

📝 Enhancement Note: For candidates from a Revenue Operations or Sales Operations background, translating their experience into a portfolio for this role might involve highlighting projects where they implemented or optimized sales tools, analyzed sales process efficiency, or leveraged technology to improve pipeline management. Demonstrating an understanding of how design impacts operational efficiency and sales outcomes will be key.

💵 Compensation & Benefits

Salary Range:

• General US Range: $150,100 - $227,000 annually (Base Salary)

• Select US Metro Areas (SF/NYC): $180,200 - $247,900 annually (Base Salary)

• Ontario, Canada: CAD 140,000 - CAD 190,000 annually (Base Salary)

• British Columbia, Canada: CAD 140,000 - CAD 192,500 annually (Base Salary) This range represents base salary only and does not include company bonus, equity, or other applicable benefits.

Benefits:

• Time Off Programs

• Medical Insurance

• Dental Insurance

• Vision Insurance

• Mental Health Support

• Paid Parental Leave

• Life Insurance

• Disability Insurance

• 401(k)

• Employee Stock Purchasing Program

Working Hours:

• Standard 40 hours per week, with an expectation of flexibility and agility to meet project demands in a fast-paced environment.

📝 Enhancement Note: The provided salary ranges are competitive for lead-level design roles in major tech hubs. For candidates transitioning from operations, understanding how design impacts operational efficiency and revenue generation is crucial. The salary bands reflect a role that is strategic and impactful, requiring significant expertise. The benefits package is comprehensive, aligning with typical large tech company offerings.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (SaaS, AI, CRM - now part of Salesforce)

Company Size: Qualified was acquired by Salesforce, a global enterprise leader. The "Design at Qualified" team is described as small and intentional, implying a focused, agile unit within a larger organization.

Founded: Qualified was founded in 2018. Salesforce was founded in 1999.

Team Structure:

• A lean and intentional design team, working with close access to product and fast feedback loops.

• Direct collaboration with engineering and ML teams, operating without a traditional "handoff culture."

Methodology:

• "Taste over process" - emphasis on strong design judgment and creative direction.

• "Prototypes over presentations" - prioritizing rapid, functional prototypes for validation and iteration.

• Speed and judgment are key craft elements, with a focus on shipping design decisions.

• Designing for AI collaborators and autonomous agents is a core methodology.

Company Website: https://www.qualified.com/ (Note: Post-acquisition, company direction will align with Salesforce's broader strategy.)

📝 Enhancement Note: The culture is characterized by agility, direct impact, and a focus on innovation, particularly in the AI space. For operations professionals, this means a dynamic environment where design directly influences how sales teams operate and how customers interact with AI-powered sales tools. Understanding the integration with Salesforce's vast ecosystem and customer base is crucial.

📈 Career & Growth Analysis

Operations Career Level: This role is a "Lead Product Designer," indicating a senior individual contributor position with significant influence and ownership. While not a direct operations role, it's critical for enabling sales and customer success operations through AI product design.

Reporting Structure: The description implies direct reporting to product leadership or a design manager within the AI product group, with very close working relationships with engineering and ML leads. The lean team structure suggests high visibility and direct access to decision-makers.

Operations Impact: The design of AI agents like Piper directly impacts sales productivity, lead engagement, pipeline generation, and customer interaction efficiency. Successful design in this role will lead to significant improvements in sales process automation, data quality within CRMs, and overall GTM strategy effectiveness.

Growth Opportunities:

• Defining Industry Standards: Opportunity to shape the future of design for autonomous AI agents in enterprise sales, a nascent and rapidly evolving field.

• Product Influence: Direct impact on product direction and strategy within a key Salesforce initiative (Agentforce).

• Skill Specialization: Deepen expertise in AI product design, conversational UX, LLM integration, and designing for complex agent behaviors.

• Leadership in a Lean Team: Grow leadership capabilities in a small, impactful team environment, influencing design culture and best practices.

• Broader Salesforce Ecosystem: Leverage the acquisition by Salesforce for potential integration with broader CRM and AI initiatives.

📝 Enhancement Note: For operations professionals, this role represents an opportunity to influence the tools and technologies that drive sales operations. Growth potential lies in becoming a subject matter expert in AI-driven sales enablement, a highly sought-after skill set that bridges design, product, and operational strategy.

🌐 Work Environment

Office Type: The role is described as Fully Remote, with a preference for candidates in the US and Canada. This suggests a distributed team environment.

Office Location(s): While the original company was based in San Francisco, the role is remote. Salesforce has numerous offices globally, but this specific role is remote-first.

Workspace Context:

• Collaborative Environment: Despite being remote, the emphasis is on close, direct collaboration with engineering, ML, and product leadership, facilitated by agile methodologies and shared ownership.

• Tools & Technology: Candidates will work with advanced AI tools, prototyping software (Figma, code, AI tools), and likely the Salesforce platform.

• Operations Interaction: While not directly in an operations role, the designer will need to understand the operational impact of their designs on sales teams, CRM systems, and GTM processes.

Work Schedule: Standard full-time hours (40 hours/week) are expected, with the understanding that flexibility and dedication are required to meet project timelines and the fast-paced nature of AI product development.

📝 Enhancement Note: The remote nature of the role necessitates strong self-management and communication skills. Candidates should be adept at virtual collaboration and comfortable working asynchronously when needed. Understanding the operational realities of sales teams, even from a design perspective, is vital for creating impactful solutions.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Review of resume and portfolio, focusing on AI/conversational design experience and prototyping skills.

• Design Challenge/Case Study: Likely a practical exercise focused on designing for an AI-related problem, potentially involving LLM behaviors or conversational flows. This may require prototyping in code or AI tools.

• Cross-functional Interviews: Discussions with engineering leads, ML specialists, and product managers to assess collaboration style, technical understanding, and problem-solving approach.

• Leadership/Team Interviews: Evaluation of design judgment, taste, cultural fit, and ability to define problems and influence product direction.

Portfolio Review Tips:

• Show, Don't Just Tell: Prioritize demonstrating your process and outcomes through case studies.

• Highlight AI/LLM Focus: Ensure your portfolio clearly showcases experience with AI, conversational design, and understanding LLM behaviors.

• Code/AI Prototypes are Key: Include examples of functional prototypes built with code or AI tools to align with the "taste over process" and "prototypes over presentations" philosophy.

• Quantify Impact: Where possible, use metrics to demonstrate the impact of your designs on user behavior, efficiency, or business outcomes, especially related to sales processes.

• Problem Definition: Showcase instances where you took an ambiguous problem and clearly defined it before presenting your solution.

• Collaboration Narrative: Describe how you partnered with engineering and ML teams, detailing the collaborative process and outcomes.

Challenge Preparation:

• Understand Autonomous Agents: Familiarize yourself with current trends and challenges in designing for autonomous AI agents, especially in sales contexts.

• LLM Behavior Scenarios: Practice designing for common LLM issues like latency, hallucinations, and varying confidence levels.

• Conversational Flow Design: Prepare to map out and design complex conversational interactions.

• Tool Proficiency: Be ready to demonstrate your skills with Figma and potentially code or specific AI prototyping tools.

• Salesforce Context: Research Salesforce's AI strategy (e.g., Einstein GPT, Agentforce) and understand how this role fits within the broader ecosystem.

📝 Enhancement Note: Candidates should prepare to demonstrate not just design skills, but a deep understanding of AI product strategy and its application in enterprise sales. The emphasis on code/AI prototyping means a practical demonstration of skills will be crucial. For operations professionals, framing design challenges in terms of operational efficiency and sales productivity will be highly effective.

🛠 Tools & Technology Stack

Primary Tools:

• Prototyping: Figma (standard), but strong emphasis on prototyping in code and AI tools.

• AI Collaboration Tools: Specific AI tooling for design, development, and iteration will be a core part of the workflow. (Candidates are expected to be fluent in these.)

• Design Systems: While there isn't a dedicated design systems team, understanding design system principles and contributing to consistency is expected.

Analytics & Reporting:

CRM & Automation:

• Salesforce Platform: Given the acquisition, familiarity with the Salesforce ecosystem, CRM workflows, and potentially its AI capabilities (e.g., Einstein) is highly advantageous.

• Automation Tools: Understanding how designed AI agents integrate with existing sales automation processes.

📝 Enhancement Note: Proficiency with Figma is expected, but the differentiator for this role will be fluency with code-based prototyping and modern AI tools used in design and development workflows. For operations professionals, highlighting experience with Salesforce, CRM integrations, and sales automation platforms will demonstrate relevant domain knowledge.

👥 Team Culture & Values

Operations Values:

• Taste & Judgment: Prioritizing thoughtful, high-quality design decisions over rigid adherence to process.

• Speed & Agility: Valuing rapid iteration, quick decision-making, and shipping functional designs.

• Direct Impact: Focusing on creating tangible value and influencing product direction.

• Collaboration & Ownership: Working closely with cross-functional teams, sharing responsibility, and fostering a "no handoff" culture.

• Innovation in AI: A passion for exploring and defining new frontiers in AI-driven product experiences, particularly for autonomous agents.

Collaboration Style:

• Direct & Integrated: Working side-by-side with engineering and ML teams, participating in problem definition and solution development collaboratively.

• Prototype-Driven: Using functional prototypes as the primary means of communication and validation.

• Feedback-Oriented: Embracing fast feedback loops to iterate quickly on designs.

• Creative Direction: Acting as a "creative director of AI collaborators," guiding the overall vision and execution of AI product experiences.

📝 Enhancement Note: The culture is fast-paced, innovative, and highly collaborative. For operations professionals, this means a role where design directly impacts efficiency and effectiveness, and where close collaboration with technical teams is the norm. The emphasis on "taste over process" suggests a culture that values intuition and expertise.

⚡ Challenges & Growth Opportunities

Challenges:

• Defining New Paradigms: Establishing novel design patterns for autonomous AI agents in enterprise sales, a field with few established best practices.

• Designing for Ambiguity: Working with complex AI behaviors (LLMs) where outcomes can be unpredictable, requiring honest and robust design solutions.

• Balancing AI Capabilities with User Trust: Designing interfaces that help users understand, trust, and effectively control AI collaborators, avoiding the "uncanny valley."

• Lean Team Dynamics: Operating effectively within a small, intentional design team that requires high autonomy and broad impact.

• Integration into Salesforce: Navigating the integration into a large enterprise organization while maintaining the agility and focus of the original Qualified team.

Learning & Development Opportunities:

• AI Product Design Specialization: Becoming a leading expert in designing for AI agents, LLMs, and conversational interfaces.

• Enterprise Sales & CRM Domain Expertise: Deepening understanding of enterprise sales workflows and CRM systems through product application.

• Influence and Leadership: Gaining experience in shaping product strategy and design direction within a significant initiative at Salesforce.

• Cutting-Edge Technology: Working at the forefront of AI and agent technology development.

• Cross-functional Skill Development: Enhancing collaboration skills with engineering and ML teams.

📝 Enhancement Note: The challenges are significant and relate to pioneering new design approaches for AI in a critical business function. Growth opportunities are tied to becoming a specialist in a high-demand area, with direct influence on product strategy and the ability to leverage the scale of Salesforce.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you designed an AI feature or conversational experience. What were the unique challenges, and how did you address them?"

• "How would you design an interface for users to shape the 'personality' or 'goals' of an AI sales agent, moving beyond a simple settings menu?"

• "Imagine Piper experiences a significant latency issue during a live sales conversation. How would you design the UI to handle this gracefully and maintain user trust?"

Company & Culture Questions:

• "What interests you most about designing for autonomous AI agents in enterprise sales?"

• "How do you approach defining problems when given a broad challenge, such as 'designing Piper's conversational presence'?"

• "Describe your ideal collaboration style with engineering and ML teams. How do you ensure smooth integration and shared ownership?"

Portfolio Presentation Strategy:

• Focus on AI Impact: Clearly articulate the problem, your design solution, and the impact of your AI-related designs.

• Showcase Prototyping Skills: Be prepared to walk through and demonstrate code-based or AI-tool-based prototypes. Explain your choices in tool selection.

• Explain LLM Considerations: Detail how you accounted for LLM behaviors (latency, confidence, failure modes) in your designs.

• Narrate Collaboration: Tell stories about how you worked with technical teams, highlighting problem-solving and integration.

• Define the Problem: For any case study, start by clearly articulating the problem you were trying to solve.

• Connect to Operations: If possible, frame your design decisions in terms of how they would improve sales operations efficiency, CRM data quality, or sales team productivity.

📝 Enhancement Note: Candidates should prepare to speak authoritatively about AI design principles, LLM behaviors, and the practicalities of building AI products. Demonstrating an understanding of how these products integrate into sales workflows and impact operational efficiency will be a strong differentiator.

📌 Application Steps

To apply for this Lead Product Designer position:

• Submit your application through the provided link on Ashby.

• Portfolio Customization: Tailor your resume and portfolio to highlight AI product design, conversational UX, and experience with LLM behaviors. Emphasize any projects involving autonomous agents or AI collaborators.

• Demonstrate Prototyping Skills: Ensure your portfolio includes examples of code-based or AI-tool-based prototypes, clearly explaining your approach and the tools used.

• Prepare Case Studies: Select 2-3 strong case studies that showcase your ability to solve complex AI design problems, particularly those related to enterprise sales or conversational interfaces. Be ready to discuss your process, decision-making, and impact.

• Research Salesforce AI: Familiarize yourself with Salesforce's current AI initiatives, such as Einstein GPT and Agentforce, to understand the broader strategic context of this role.

⚠️ 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. The role is for a Product Designer, but its focus on AI agents impacting sales workflows makes it highly relevant to those interested in Revenue Operations and Sales Operations enablement.