System Architect, New Products

About Wispr

Wispr is an AI research and product company building the voice interface for computing. AI can now reason, code, and act. Yet, humans still do the work of the interface. We think that’s backwards.

Our first products are Flow, which lets you speak naturally in any application, and Notetaker, which builds context across conversations. We’re building toward an interface that can perceive, understand, and take action with earned trust. That means solving hard problems across models, systems, and product - and caring about the final human experience as deeply as the technology underneath it.

We’re a talent-dense team that holds strong opinions, tests them quickly, and builds technology that sparks joy. Our goal is to build the first voice interface used every day by a billion people.

About the role

You’ll create core building blocks for AI product concepts that the team can dogfood and build on. You’ll shape a reference architecture around models, live context, memory, tools, agent harnesses, and durable execution, making crisp calls about what belongs in each layer. You’ll decide which components should become general platform primitives that other teams can adopt.

What you’ll do

• Build shared platform primitives for agentic systems development, such as memory, context management, tools, and background execution.

• Create infrastructure for prototyping, training, and evaluating models, with reusable environments and developer tooling.

• Develop systems for triggers and context capture across devices, surfaces, and modalities.

• Design harnesses and primitives for coordination and execution handoff between models.

• Make these systems reliable and production-ready through observability, recovery, security, and latency and cost controls.

You may be a fit if

• You’ve designed and shipped a significant greenfield system from an ambiguous problem through production use, then evolved it based on real failures and usage.

• You’ve built shared primitives that multiple teams adopted and made deliberate choices about abstraction boundaries and developer experience.

• You’ve owned backend or distributed systems with critical scaling and reliability requirements.

• You start design from the user experience and its latency, quality, privacy, and trust requirements.

• You’ve created alignment across product, ML, client, and infrastructure teams, communicated architecture and tradeoffs clearly, and driven decisions to closure.

You do not need to have trained foundation models, built a low-level inference stack, or worked in every domain above. Exceptional depth in backend and platform systems, the ability to learn adjacent areas quickly, and demonstrated architecture-level ownership are what matter.