The ProblemIndependent freight agents are the backbone of a $600B industry. They run $2-50M books of business, often from a home office, and they live in software all day: covering loads, sourcing carriers, quoting, chasing new shippers, and handling back-office work. Almost none of that software was built for them. It was built for large brokerages with IT departments.
The client is an AI-native parent brokerage that provides agents with hands-on support and tools to scale revenue without adding headcount. The client's first handful of agents already represent $800k+ of ARR, a few months after the client moved its first load. The product supports their core workflows today, but freight is messy, and the list of problems the client hasn't solved yet is long.
The RoleYou'll own features end to end: talking to agents, deciding what to build, designing the interface, writing the backend, and shipping to production. Nobody hands you specs or mocks. You'll work as a peer to the client's Product Lead and two Founding Engineers, sharing ownership of what the client builds and how it works.
For example, you might figure out how a dispatcher should triage forty loads before 9am, build the interface and the services behind it, and put it in agents' hands the same week.
This is a good fit for a strong engineer who has had a taste of product work (scoping a feature, running user sessions, making the design call) and wants a role where that's the whole job, not a side quest.
What You'll Do- Deeply understand the highest leverage problem: Sit with agents and watch them work. Understand their economics, the workflows that waste their time, and where they reach for a spreadsheet or the phone instead of the client's product. Sit with product to turn that into a point of view on what to build next.
- Design and build it: Ship complete features across the stack: interface, API, data model. In some cases, you might define and ship an interface and partner with another founding engineer responsible for AI agents.
- Ship and learn: Get work into production fast, watch how agents actually use it, and iterate to help them improve their outcomes.
- Set the bar: Establish the shared components, interface patterns, and visual language that future features build on.
- Work AI-first: Use AI throughout your work: research, prototyping, design exploration, code, and testing. Help the client figure out where AI belongs in the product itself, not just in how the client builds it.
What Success Looks LikeSix months in, you've shipped dozens of features that agents use every day and would notice if they disappeared. You can point to specific workflows that are measurably faster or more effective because of your work. And the product feels more coherent than when you arrived, because the patterns you set are the ones the rest of the team builds on.
What the Client Is Looking ForStage fit matters more than years of experience. This is the hands-on, sit-next-to-the-users, own-the-whole-thing version of the job.
- You ship full-stack: You can take a feature from the data model to the interface on your own, and handle edge cases without being asked.
- You've built tools for professionals: Dashboards, admin tools, internal ops software, vertical SaaS: dense interfaces where users need to act quickly and accurately.
- You have product judgment and want to use more of it: For anything you've shipped, you can explain what the user was trying to do, what you tried first, and why the final version worked better.
- You're deeply AI-native: AI is how you work, not a tool you occasionally reach for. You can walk the client through your actual workflow, where it makes you faster, and where it fails you.
- You have deep user curiosity: You'd rather watch an agent work for an hour than guess at requirements.
- You're high ownership: You treat the product like it's yours, and do whatever it takes to make the client's customers succeed.
Backgrounds That Might Fit- A full-stack engineer who has had a chance to do some product work and wants to do more
- A design engineer who goes deep on the backend, or a backend engineer with strong UI instincts and taste
