Product Builder, Growth

Alt is unlocking the value of alternative assets, starting with the $5 B trading-card market. We let collectors buy, sell, vault, and finance their cards in one place and we are backed by leaders at Stripe, Coinbase, Seven Seven Six, and pro athletes like Tom Brady and Giannis Antetokounmpo. Our next frontier is real-time pricing at scale—the Alt Value that powers every trade, loan, and product on the platform.

The Role

Alt is growing! This role leads the charge on new user count: how many collectors land on Alt, how many make a first submission or a first bid, and how many come back without being asked. That number is the job. Everything else in this description is downstream of it.

This is a builder seat, not a product management seat. You own the seller submission funnel, buyer search and discovery, and the experimentation infrastructure underneath both, and you own them the whole way: you find the drop-off, you write the code, you ship it behind a flag, you read the result, you keep it or you kill it.

What this role is not: writing PRDs for someone else to implement, running roadmap ritual, managing a pod, or translating between engineering and the business. If that's the shape of your last five years, this probably isn't the right fit, and we'd rather say so up front than waste your time.

What it is: pulling the funnel yourself in SQL on Monday, shipping the onboarding change on Tuesday, standing up the experiment harness that makes Wednesday's test trustworthy, and putting a model behind dealer reactivation instead of a campaign.

You report directly to the CEO. If you want a CEO in the build with you, this is that. If you want distance from the top, it isn't.

The metrics you own: Submission Volume (weekly, by seller segment) and Search-to-Bid Conversion. Supporting KPIs: Snap to Sell activation rate on first submission, seller reactivation rate among dormant sellers, daily active search query volume, listing rate (vaulted inventory live on marketplace), ship-and-decide velocity (changes shipped and tests called per week), and dealer segment submission frequency and GMV.

The people who are great at this have run growth inside a system that was already working, not just inside a roadmap someone else set. They ship their own code. And they are participants in this market: they buy, they sell, and they have a view on where liquidity actually goes.

What You'll Own

• The submission funnel, end to end, in code. From a seller's first submission to a high-frequency, high-value one. Find the drop-offs across onboarding, Snap to Sell, quote acceptance, vault intake, and resubmission, then ship the fixes yourself. Build the experiences that activate dormant sellers and raise dealer submission frequency without anyone having to send a message.

• Search, discovery, and buyer conversion. Search quality, card discovery, and browse across the platform. Move search-to-bid through ranking, filtering, recommendations, and real-time Alt Value pricing context. You'll be in the ranking code, not describing it. Right card, right buyer, right moment.

• The experimentation harness. Build it, don't request it. Assignment, exposure logging, guardrails, readouts, and decision rules, wired to the warehouse and fast enough that a test is a Tuesday decision. Then run high-velocity tests on it across onboarding, activation, search, and submission, and leave behind a compounding library of what we learned.

• Marketplace liquidity and supply-demand balance. Watch submission volume, listing rate, bid depth, and sell-through. Find the imbalances by card category, price tier, and seller segment, then build the product that fixes them. Use Alt Value as a growth lever: surface the market signal that makes someone act.

• The bets and the trade-offs. A short quarterly plan tied to submission volume, buyer conversion, and time-to-liquidity, and a weekly record of what actually shipped. Work shoulder to shoulder with Engineering, Design, Data, Lifecycle, and Ops. Operate on the funnel detail and the experiment result, and on which bets we're making and why. Communicate the trade-offs to the CEO plainly.

What Great Looks Like (6 Months)

• You've been shipping to production since week two, and the team reviews your PRs the way they review each other's.

• Weekly submission volume is measurably up, driven by changes you built rather than by headcount or outreach.

• An experimentation harness you built carrying 3 to 5 concurrent tests across growth surfaces, trusted enough that people stop arguing about the numbers.

• Snap to Sell activation rate meaningfully improved through onboarding and flow changes you shipped.

• Search-to-bid conversion up through better ranking, discovery, and Alt Value pricing context.

• Dealer reactivation running as a model decision, not a campaign, with no manual outreach behind it.

• A thin, live plan that Engineering, Data, and leadership actually use to prioritize, and that gets rewritten when the data says so.

How You'll Use AI Here

We don't want to hear that you use Claude every day. Everyone does. We want to know what you've built with it. Concretely, in this role:

• Build the experiment readout as an agent: it pulls the test, checks the guardrail metrics, flags the confound, and writes the ship-or-kill recommendation you then argue with

• Run model-driven ranking and relevance experiments on search, using Alt Value and behavioural signal to decide what surfaces, measured against search-to-bid rather than click-through

• Make dealer reactivation a model decision, not a campaign: which seller, which trigger, which cards, what timing, drafted and personalized without a human in the loop

• Put an MCP server over PostHog and the warehouse so "where did first-submission activation break last week, by segment" is a question you ask in a sentence

• Build the flow yourself in Claude Code or a vibe-coding tool, put it in front of a real dealer, and ship the version that survives that

If you've built agents, written skills or MCP servers, wired up connectors, or shipped internal tooling your team actually depends on, lead with that.

What You Bring

• You ship production code. Not "technical." Not "I can read code." You open the pull request, you take the review, you own the on-call consequence. Full-stack enough to move through a growth surface without a handoff: the frontend flow, the API, the query, the job.

• You've owned a growth surface, marketplace funnel, or PLG motion and moved the number on it. Roughly 5+ years of building, but we're reading the work, not the years.

• You own a number today and can name it, its baseline, and where you took it, on the first ask.

• Strong data fluency. SQL and Python, plus PostHog, Amplitude, Mixpanel, Statsig, Eppo, or similar. You pull your own numbers and you've built the instrumentation behind them.

• Experimentation in your hands, not on your résumé. You've designed the test, set the decision rule before it ran, and made the call on partial data.

• Deep understanding of two-sided marketplace dynamics. Supply and demand, liquidity, and what happens to one side when you push the other.

• You've built real things with AI, not just used it. Agents, skills, MCP servers, connectors, internal tooling people depend on.

• Scrappy and high-ownership. You communicate with precision, you move without hand-holding, and you go find the problem rather than waiting for the brief.

This Probably Isn't For You If

• You need requirements to arrive before you can start.

• Your best work happened inside a well-run PM, design, and engineering machine, and you're looking for a more structured one.

• You'd hand the prototype to an engineer. Here, the prototype is how the argument gets settled, and you build it.

• You're excited to manage before doing. This is a builder's role first. The org grows around people who deliver.

• You want to own the roadmap more than the outcome.

How We'll Interview You:

We'll be specific so you can prepare. Before any of it: download the app, put a card up, make a bid, or sell. Every round assumes you've used the product, and we expect your point of view to sharpen as you go.

1. Recruiter screen- 30 minutes via google meet. The metric you own today, the last thing you shipped yourself, why Alt specifically, and how you're actually using AI. We'll answer your questions and align on comp.

2. Hiring manager with Leore, our founder and CEO, 30-45 minutes. This role reports to Leore, so he runs the hiring manager round himself. Go deep on a funnel you owned: the baseline, where you took it, what you built, and the experiments that worked and the ones that didn't.

3. Team Interview, 2- 45 Minutes sessions. The engineers and data partners you'll ship alongside. How you work in a shared codebase.

4. Build walkthrough- 45-60 minutes. Bring one thing you built and shipped, a repo, a PR, a live URL, an internal tool, an agent or skill you wrote, and open it on screen. What problem it solved, what's ugly about it, where AI helped and where it got it wrong. Then we go deep on a funnel you owned: the baseline, where you took it, what you shipped. Rough and real beats polished and hypothetical.

5. Executive interview, 30 minutes. The closing conversation. What you'd go after first, what you'd deliberately not do, and whether this is the job you actually want.

6. Reference check(s), 15 minutes with a former manager(s)

Compensation: $200,000 - $250,000 per year, plus equity for all full-time employees.

What we offer:

For full-time Employees

• We cover 85% of your medical, dental, and vision, and up to 50% for dependents. HSA/FSA available

• Generous PTO that people actually take

• Parental leave at full salary

• $200/month wellness + $100/month home office stipend

• Free DoorDash Pass membership, because dinner shouldn't be a decision

• Remote-first (for most positions), with WeWork access when you want a room with other humans

• 401(k)

• Alt Equity to all full-time employees