Forward Deployed Engineer

Forward Deployed Engineer New York City HQ ᐧ Full time ᐧ On-site ᐧ R&D ᐧ $140K-$180K + meaningful equity Prior to Ekho, one of the largest retail segments in the world had no checkout button. If you wanted to buy a vehicle online, the best you could do was fill out an “I’m Interested” form and wait for someone to call you back. Found the bike of your dreams at a dealership two states away? You were mostly on your own. Tax requirements, titling workflows, and registration rules vary by state and county. Most dealers didn’t sell across state lines at all, because they had no reliable way to do it. Now they can. A buyer finds a bike, clicks “Buy Now,” completes financing and insurance verification online, and gets it delivered to their door in a few days. The whole thing takes as few as ten minutes. And the dealer doesn’t have to be at their desk (let alone awake) for any of it. The first time one of our dealers woke up to a completed overnight sale, they messaged us: “Oh my God, this is crazy. We just fulfilled a transaction while the whole team was asleep.” We get messages like this regularly now, and they’re no less exciting than the first one was. What made it possible was 18 months of untangling a combinatorics problem disguised as county-specific titling and registration, and integrating with 50 DMVs that still prefer faxes to APIs. That foundation is built. Now we’re putting AI on top of it, expanding into cars, and building the transaction layer that works in-store as well as online. One thing worth saying directly: Anthropic can’t ship something tomorrow that makes this company obsolete. The moat is the foundation beneath the code: the 50-state compliance framework, the DMV relationships, and the legal licenses we’ve secured. That’s not something you can prompt your way around. Unlike most startups right now, we’re not racing against the next model update. Where you’ll spend your time Here’s what a typical week might like (though we can guarantee no two weeks will look the same): About half your time might go to client onboarding: figuring out the right integrations with the vendors a new dealer already uses, configuring fee logic that’s never quite the same twice, building sandbox buyer portals so dealers can experience their own checkout flow before going live. The other half comes from dealers themselves: feature requests, feedback, and problems that surface once they're actually using the product. A dealer sees something during a walkthrough and asks for manufacturer rebates displayed automatically. Another wants insurance verification handled via a direct call with the provider instead of an automated check. You scope it, build a V1, and figure out what it looks like at scale. The most interesting integration in the queue: getting Ekho’s fee logic to speak Lightspeed’s language—the inventory management system most of our dealers already run. You’ll work inside the core payment system, understand how it currently models fees, figure out how to extend it accurately, build a settings UI for dealer configuration, and make sure the logic holds across every edge case… all while a dealer is waiting to go live. You’ll be touching payments infrastructure, product, and client-facing configuration simultaneously. Our first car dealer went live a few weeks ago. By end of year, the goal is an in-store transaction layer: iPads on the showroom floor where a buyer who just test-drove a bike can complete the full purchase without touching a piece of paper. The FDE who joins now will be in the room when we figure out what that looks like. Your mandate is to own the client relationship technically, from first integration through ongoing development, and make sure everything you learn from clients feeds back into the platform—including identifying what should eventually be self-serve so that onboarding scales without always requiring a human in the loop. Who you’ll work with Rowan grew up in South Africa, where his dad owned a used car dealership. Chris grew up in Atlanta, and was close family friends with some of the largest dealer operators in the Southeast. They met at Stanford, went to see what good looked like at scale (Rowan at Duolingo, Chris at Meta), then went through YC determined to find the most overlooked problem in the largest industry they could. This one—a $2 trillion industry that couldn’t complete a sale online—was the one that stuck. Bongi , our VP of Eng, has known Rowan since high school. He turned down several of Rowan’s ideas before finally saying yes to this one. That kind of conviction from someone who knows the founder well enough to say “no” is its own kind of signal. Nisarg and Charlie co-lead our Client & Product success team together. They met at UNC and when they’re not busy rooting on Carolina’s basketball team, they love engaging with our customers to understand what products and experiences will have a profound, lasting impact. We’re 34 people, mostly in our mid-to-late twenties, with backgrounds across Stanford, YC, BCG, Goldman, and Meta. Nine of us are engineers. We spend four days a week together in our Flatiron office. Nadim has kept every laptop from every job he’s ever had. They’re now racked in a server farm in his apartment running AI agents (before that it was crypto). David edits a sci-fi publication online and curates the strangest stories you’ve ever read. Alexis is working on becoming a DJ and producer (his genre is deep house). Jon studied film and posts photos to Slack that make everyone else’s iPhone photography look like a crime. Rodrigo can find the Spanish speakers in any room in New York, which is its own kind of superpower. Mike is our industry vet. He’s in sales, not engineering; but you'd never guess it from the Claude Code usage. He spent decades as an executive at Triumph, Piaggio, and Zero Motorcycles, and recently organized a motorcycle track day for the whole team because he found a free event and figured people would want to go. (They did.) There’s a gong in the middle of the office that goes off without warning every time a sale closes. Engineering debates here are about architecture decisions, ownership boundaries, and what to name things. The naming convention debates alone have generated Slack polls with 15+ options, many of them so bad they’re good. The founders have never said “my way or the highway.” Engineers define what to build and why , not just how . The whole team has an unlimited Claude Code budget, and it’s not just an engineering thing. People across the company are shipping with AI. Who’ll thrive here You came up through CS or a technical STEM field and have some real engineering behind you (not closing tickets, but owning outcomes). Unfamiliar codebases don’t intimidate you; they’re just puzzles you haven’t seen yet. Client conversations don’t feel like a tax on the real work. They’re where the real work comes from. You’re AI-native in practice. You have Claude terminals open; you’re running agents. You move faster than people who aren’t. You don’t mind long hours when the work is worth it. The team is in at 8:30; dinner gets ordered at 7 for whoever’s still here, and most days, most people are. You’re looking for a place to build, not a place to settle. Two years from now, you could be leading a larger FDE team, moving into product engineering, or owning a book of client accounts. All three are real paths. Stack : React, Node.js (serverless), Express.js, NoSQL Tools : GCP, Firebase, Retool, Stripe, and various SaaS platforms Compensation & benefits $140K-$180K base Meaningful equity Health, dental, & vision 401(k) Free lunch and dinners $700/year work setup stipend Annual team offsite How we hire After an initial screen with our recruiting team, you’ll have a call with Bongi, and a separate call with our Client and Product Success team, because how you communicate with non-technical stakeholders matters as much here as how you code. Then there’s a technical interview with Chris. The onsite is where it gets interesting. You’ll have two technical challenges to work on, and they're deliberately different. The first: build something from scratch, with full access to AI tools. The second: debug and fix issues in an existing system, with AI turned off. We designed it this way because the job requires both knowing how to move fast when you’re building new things, and knowing how to reason through a system when the scaffolding isn’t there to help you. After that, lunch with the whole team, and a conversation with Rowan. We move fast when we find the right person. And we respect your time enough to be honest if it’s not a fit.

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