The job

An engineer that designs the experience of working with agents. You own how Bonsai looks, feels, and behaves across the product: the visual direction of every screen, the interaction language that ties those screens together, and the core agentic flow and chat conversation. You decide when an agent’s answer should be text, a component, a structured result, or something else, then design and build the system that makes those choices feel coherent. You take ideas from first principles to a polished experience in code and iterate with users.

Problems you’ll work on

These are examples, not lanes. You will move between them, while taking real ownership of the ones that match your interests.

One product across many surfaces: Bonsai includes sessions, skills, memory, plugins, and workflows. Each can be useful on its own, but people should feel they are using one product. How do you create a visual and interaction language that holds together as the surface area grows?
The right shape for an agent’s work: An agent might answer with prose, a list, a table, a form, a timeline, or an interactive surface. When should each be used? How much should be visible now, and what should stay one step away?
A conversation people can trust: People need to understand what an agent is doing, steer it while it works, review its output, and recover when it fails. How should streaming answers, tool calls, approvals, parallel work, and uncertainty feel in the core chat?
A system people and agents can extend: Engineers, PMs, plugins, and agents all create UI. How do you encode enough visual and interaction judgment into tokens, components, examples, and checks that new work feels like Bonsai by default?

What you’ll do

Set visual direction across the product: typography, color, layout, density, motion, and the quality bar for every screen.
Design and build core agentic flows: chat, streaming responses, tool calls, approvals, progress, errors, and the points where a person takes control.
Define how agent output becomes interface: choose when to use text, components, structured data, or another interaction, then build the primitives and patterns that make the choice consistent.
Build cross-screen UX patterns that make depth easy to reach. Day one should be simple. Day thirty has serious depth, and it still feels simple.
Own the design system and its operating layer: components, tokens, prototyping tools, examples, and visual or accessibility checks that keep the product coherent.
Prototype quickly in the real system, test with users, and turn what works into production code that other people and agents can build on.

Who you are

You are comfortable being both designer and engineer. You care about product quality at the level of visual direction, interaction details, and shipped code.
You design in code. You can build polished, accessible frontend systems without waiting for wireframes, and you know when an abstraction helps or gets in the way.
You can hold the whole product in your head. You notice when two screens teach different mental models, and you know how to bring them back together.
You have strong instincts about interaction design: hierarchy, timing, progressive disclosure, feedback, and the difference between an answer and an interface.
You use agents heavily and have opinions earned from real work about what makes AI interaction clear, useful, and trustworthy.
You have taste, and you can explain why the version you kept beat the ones you threw away.
You are comfortable with ambiguity. The design language, agent patterns, and product conventions are still being made.

Bonus

You’ve designed and shipped a desktop app.
You’ve built a design system, prototyping tool, or visual verification workflow used by other engineers.
You’ve worked on agentic products, developer tools, or another product where the interface is part of the core technology.

About Yaklabs

Yaklabs is building a desktop AI application that turns knowledge workers into AI power users, without docs, API keys, or knowing what to ask for. One surface for agentic AI work: proactive, personalized, progressively powerful. The gap between AI power users and everyone else isn’t talent, it’s setup. We close it.

The team: Alex Goddijn spent four years at Palantir, then founded an agent harness company that was acquired by Poolside AI. Seb Goddijn led internal AI at Ramp. We’re building Bonsai so that kind of leverage isn’t limited to companies with their own internal AI team.

We have funding. Product and design work in person in New York City, and some engineering roles are remote. Small team, high intensity, no passengers.

Who we look for

Technical builders with a domain edge. Everyone here is technically minded and can build and ship. You bring a distinctive strength in a domain: design, systems, product, infrastructure, or another area, and use it to take a problem from first principles to working software.
First principles thinking. We’re building in a category that’s being defined in real time. Best practices don’t exist yet. You reason from the problem, not from what everyone else is doing.
High agency and ownership. You don’t wait to be told what to do. You see what needs to happen, you go make it happen, and you own the outcome. At a team this size, there’s nobody to delegate to.
Deep curiosity about AI tooling. Not just using ChatGPT or Copilot: you’re experimenting, writing your own tools, trying new agent frameworks the week they drop, forming opinions about what works and what doesn’t. The people building this product should be the most demanding users of the category. If you’ve shipped PRs to open-source agentic harness projects, tell us.
You build compounding leverage. In the era of building with agents, one person doesn’t just ship one person’s work, they build the systems that build the product. Every person is amplified, and with that amplification comes the responsibility to build things that compound: skills, automations, agent workflows that make the next thing faster. This is a new way of working, and you’re excited to develop the skillset it demands.

The deal

Early team. $215k to $325k base salary for US-based hires, plus meaningful equity.
In person in New York City for product and design roles. Some engineering roles are remote, and each posting lists its location.
You’ll shape the product, the culture, and the company. This is a founding-team role.

YakLabs is an equal opportunity employer. We consider every application without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic. If you need an accommodation at any point in the process, email careers@yaklabs.ai and we will work it out with you. A person, not a machine, reads every application.

Yaklabs

Latest Jobs

Product Engineer: Agentic UX