The first surface is Piper's brain: how Piper understands a lead, forms a plan, and explains its reasoning. You'll design the interface for shaping its personality, goals, and objection handling. Not a settings panel. Something closer to a thinking partner you can tune.
The second is Piper's live presence, the chat and video experience where the AI is the rep. The work is in the details: the micro-interactions, latency handling, turn-taking, and tone that make it feel credible instead of uncanny.
The design patterns for autonomous agents in enterprise sales are still being figured out. You'll be part of that.
How you work
Taste over process. Prototypes over presentations. Speed is a quality, judgment is the craft. You think of yourself as a creative director of AI collaborators, not a solo craftsperson. Concretely:
You prototype in code or with AI tools, not just Figma
You're faster with agents than most designers are without them
You ship design decisions, not just document them
Requirements
6+ years of product design, with at least 2 years on AI or conversational experiences
You understand LLM behavior (latency, streaming, confidence, failure modes) and design for it honestly
Fluent in AI tooling as a core part of how you work, not an experiment
Strong visual and interaction craft. You have taste.
Comfortable without a detailed brief. You define the problem alongside the solution.
Works directly with eng and ML. No handoff culture here.
Voice, video, or real-time communication design background
Familiarity with enterprise sales or CRM workflows
The design patterns for AI agents in enterprise sales are still being established. You'd be one of a few people defining them at production scale, on a product that's already live and growing.
Ownership here is genuine. You'll work directly with leadership, influence product direction, and own your work from problem definition through ship. No gatekeeping, no waiting for a brief.
The Salesforce acquisition puts our work in front of one of the largest enterprise customer bases on the planet. It is important that the team remains nimble and autonomous to keep innovation moving.
Applications will be accepted until June 15, 2026
At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.
The typical base salary range for this position is $150,100- $227,000 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $180,200 - $247,900 annually.
For Ontario-based roles, the base salary hiring range for this position is CAD 140,000 to CAD 190,000 annually.
For British Columbia-based roles, the base salary hiring range for this position is CAD 140,00 to CAD 192,500 annually.
The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.
This posting is to fill
Benefits
Equity / stock optionsPerformance bonus
Additional Information
Qualified has been acquired by Salesforce! View the press release:
https://www.salesforce.com/news/stories/salesforce-signs-definitive-agreement-to-acquire-qualified/
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
Qualified has been acquired by Salesforce! View the press release: https://www.salesforce.com/news/stories/salesforce-signs-definitive-agreement-to-acquire-qualified/
Design at Qualified
Design at Qualified is small and intentional. There's no design systems team or research ops function, just close access to the product, fast feedback loops, and problems that rarely have obvious solutions.
Most of those problems are about AI where the interface is rarely the hard part. The challenge is helping users understand what the AI is doing, trust it when it's right, catch it when it's wrong, and shape it toward what they actually need. That takes judgment more than process.
We're building Piper, an AI SDR that runs autonomous sales conversations, follows up with prospects, and moves pipeline without a human in the loop. Piper is not a chatbot and not a copilot. Piper is an agent. You will work on two of its most interesting surfaces: the AI brain (how Piper understands prospects and explains its reasoning) and conversational presence (the live chat and video experience where the AI is the rep).