Senior Product Designer - Meeting Lifecycle

Read AI, Inc.•Seattle, WA

6d•$160,000 - $190,000•Hybrid

About The Position

At Read AI, we’re redefining how teams collaborate by bringing intelligence to every conversation. Our platform supercharges productivity across meetings, messages, and email—so work gets done faster, smarter, and with better focus. We integrate seamlessly with tools like Zoom, Microsoft Teams, Google Meet, Slack, and more, helping teams stay aligned whether they’re in the same room or across time zones. Backed by $81M in funding from Smash Capital, Madrona, and Goodwater Capital, Read AI is building the future of AI-powered collaboration. We believe great AI products require clarity, trust, and craft—and design plays a foundational role in making that real.

Requirements

5+ years of product design experience. We weigh the scope you have owned more heavily than the year count, but this role assumes you have already been the design owner of a hard problem area - not only a contributor to one
Independent ownership of a complex product area in a shipped product, with a portfolio that demonstrates strong interaction and visual craft
Experience designing multi-state experiences where edge cases, failure modes, and recovery paths are central to the problem
Systems thinking that creates coherence across surfaces and mechanisms without flattening everything into one pattern
A track record of shaping product direction, not only executing briefs
End-to-end ownership from problem framing through launch and evaluation of whether the work succeeded
Strong partnership with Product and Engineering, including the ability to influence scope, navigate disagreement, and carry design quality through implementation
Comfort working through technical constraints and the judgment to distinguish real limitations from inherited assumptions
Ability to prototype complex behavior so teams can respond to real interactions rather than static screens
Fluency with AI-assisted design workflows and sound judgment about where AI improves—or weakens—a product experience
A multiplier mindset: PMs, engineers, and designers seek your perspective, and the quality of the team’s work improves because you are part of it

Nice To Haves

Experience with media capture, recording, streaming, transcription, or playback
Familiarity with permissions, background processes, connectivity, synchronization, or long-running application state
Experience with privacy-sensitive or multi-party products
Experience designing real-time, probabilistic, or AI-generated output
Experience designing accessible, low-attention, or peripheral interfaces
Direct experience with meeting software is not required. We care more about evidence that you bring clarity, craft, and sound judgment to a complex, trust-sensitive product.

Responsibilities

Design how Read becomes ready, starts, pauses, recovers, and completes capture across desktop, mobile, web, bots, and native platform integrations
Define how Read communicates its state so users can tell it is working without leaving the meeting
Keep the meeting—not Read—as the user’s primary focus
Design what happens when permissions are denied, platforms restrict access, or capture is interrupted or partial
Make clear what was preserved, what was missed, and what the user can do next
Help users create a useful meeting record from notes, whiteboard photos, files, and externally recorded media without implying that Read heard something it did not
Design disclosure, consent, notification, objection, and opt-out experiences
Balance transparency for participants with keeping the meeting focused and usable
Work through the competing needs of the Read user, host, other participants, enterprise administrators, and platform providers
Define one customer-facing model for capture state that holds across surfaces
Decide what must remain consistent and where platform-specific patterns are the better answer
Design for cases where capture mechanisms compete, conflict, or produce duplicate records
Shape live in-meeting assistance: notes, questions, and retrieval designed for latency, uncertainty, and revision, with a clear line between preliminary live content and the finished record.