Backend Engineer

Channel3Database of every product on the internetBackend Engineer$120K - $200K•0.25% - 0.75%•New York, NY, USJob typeFull-timeRoleEngineering, BackendExperienceAny (new grads ok)VisaUS citizen/visa onlyConnect directly with founders of the best YC-funded startups.Apply to role ›Alexander SchiffCEOAlexander SchiffCEOAbout the roleWhat we're building Channel3 is building a database of every product on the internet — structured data that lets AI agents understand, compare, and shop.

We plan to become the central node of agentic commerce, powering every AI transaction and taking a cut of GMV. We see Channel3 becoming as foundational to AI commerce as Stripe is to payments or Plaid is to fintech. Why now AI became smart and cheap enough to structure the world's messy product data. Agentic commerce is projected to drive $3–5T globally by 2030, and it's bottlenecked by bad data.

The founders Alex (CEO) and George (CTO) have been friends since the first day of Duke. Alex began coding at 9, started his first company at 12, and most recently led AI projects at studio.com, where he got this idea. George published research on automating astronomy with robots at 18, and worked on big-data problems at Palantir for the past 2 years. Unfortunately, we are not able to sponsor visas at this time.

You must have authorization to work in the US. Our progress so far We’ve indexed 100M+ products 2,000+ developers have started using our API We’re scoping pilots with some serious enterprise customers We’ve partnered with 5,000+ brands, including Walmart, Best Buy, and Home Depot What you’ll do Write code to understand 1B products. We stitch together the latest language, embedding, image, and segmentation models to build a true understanding of each and every product.

Product pages vary greatly across retailers. We’ve built a computer-vision system that can understand any PDP, with no custom code or manual intervention on any site. Deduplicating products across merchants is really hard. Products are described differently, often have different images, and almost never have stable identifiers. We use multimodal models to help us understand different products and match them.

Understanding what variants a product comes in might be even harder. We want to know what colors and sizes every shirt comes in, and what configurations customers can order for a new couch. Build world-class search. Developers should be able to find “outdoor grills from Weber, less than $1000, with 4 burners,” “running sneakers under 300g, size 12,” or “this couch [image] but in green” — in under a second.

Embeddings don’t get us there. We’re always looking to add structured data that lets developers construct powerful queries with deterministic filters. Lately, we’ve been ideating about how to return “good” results, which we’ve learned is not just the highest keyword/semantic match. Engineer for reliability and cost. Create evals to measure drift, and guardrails to prevent regressions and hallucinations.

Be clever and scrappy to reduce database cost and token usage everywhere we can. We use billions and billions of tokens a month, mostly on open-source models. We embed every product, we look at every image with AI, and we run dozens of calls per product — it’s necessary, but it adds up. We’re always looking to reduce token usage, rely on a smaller model, or do some clever context engineering to reduce input tokens.

We structure the world’s product data — and we have to store it and search through it (both internally to find matches and to power our API). We’ve taken many steps towards making this economical, and will continue to do so. Why join us The time is right: AI is finally smart and inexpensive enough to make a universal product graph technically possible; agentic commerce creates immediate demand and a clear monetization path.

We’re moving fast: We’re up and running, with 2,000+ developers building on our API, customers eagerly awaiting features, and 25M+ products processed every day. You’ll have direct ownership of technical and infrastructure decisions, roadmap, and prioritization. You’ll help us grow the team and build our culture from the ground up. We’re having lots of fun: We enjoy working together, we take pride in building really good tech, and we all look forward to coming to work each day.

How we work We work out of our sunny office in Flatiron in-person together Monday through Friday. We provide dinner Monday-Thursday, plus any snacks you want (we’re across the street from a Trader Joe’s). Investors We raised a $6M seed round in August 2025, led by Matrix (Apple, FedEx, Afterpay, Oculus) with participation from Ludlow (Honey, StockX), Y Combinator, Paul Graham, a16z + Index scouts, and a dozen angels (mostly ex-YC founders).

About the interviewSend us a short message telling us one of the following: What’s one thing you’re curious about re: how Channel3 works? What's something you're actively learning right now, either for work or just for fun? How are you going about it? If you’ve used Channel3 before: What did you like? What was confusing? What would you like to change about it? No need to write more than a few sentences, but please do put a little thought into this — it goes a long way!

If we think you could be a good fit: We reach out and set up a 15 minute chat You do a short take-home programming assignment, then show us what you made We try working together for a day or two in NYC We send you an offer! About Channel3Channel3 is building a database of every product on the internet. Our API lets any AI app or agent add shopping capabilities and earn commission on sales. We’re based in NYC, backed by Matrix, Ludlow, and Y Combinator; you should apply if you want to build the foundations for a brand-new kind of commerce.

Channel3Founded:2025Batch:S25Team Size:5Status:ActiveLocation:New York City, NY FoundersGeorge Lawrence FounderGeorge Lawrence FounderAlexander Schiff CEOAlexander Schiff CEO