Real-Time Auction Systems Engineer

Alt Co.; Polska; Hybrid; PLN 240,000 - 340,000; Full time

Benefits offered by this job

Health insurance

Wellness stipend

Home office stipend

DoorDash membership

Remote-first

401(k)

Equity

Job summary

Alt is building real-time auction and listing systems for high-value collectibles. You will own the low-latency backend and the UI surfaces that drive nine-figure GMV, from bid resolution to front-end dashboards. The role emphasizes high concurrency, AI-powered valuation, and discovery.

You’ll mentor the team, shape architecture, and ship production-grade features used by thousands of collectors. Join a remote-first, equity-enabled team with strong backing and a focus on reliability and

Qualifications

• 5+ years building and scaling complex applications.
• Proficient in Python, PostgreSQL, and AWS.
• Experience with high-concurrency systems and real-time features.

Responsibilities

• Own the auction engine and high-concurrency bidding system.
• Develop AI-powered liquidity features.
• Build personalized discovery and matching for collectibles.
• Create seller tooling and analytics for power-sellers.
• Own end-to-end system from backend to UI.
• Mentor the team and set code quality standards.

Skills

Python

PostgreSQL

AWS

Distributed systems

Tools

Docker

React

TypeScript

Job description

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

The last ten seconds of an auction are the whole product. Hundreds of people who have been watching one card for a week all arrive at once, every one of them refreshing, every one of them bidding.

That's this job. You build and scale the high-concurrency bidding and listing systems behind nine figures of annual GMV, and you build the surfaces on top of them. Not one or the other. The low-latency backend logic that resolves a bid and the responsive real-time UI where a collector watches it land are the same feature, and they're both yours.

The number this team is measured on: auction GMV. Every system here either moves it or protects it.

What You'll Own:

• The auction engine. Build and scale the high-concurrency bidding and listing systems that power nine-figure annual GMV. Thundering herd in the closing seconds is a design constraint, not an incident.

• AI-powered liquidity. Develop the next generation of features that use AI to give consignors and sellers instant valuations and upfront liquidity. Being wrong here costs money, which is what makes it interesting.

• Personalized discovery. Use data and machine learning to match unique, one-of-one collectibles to the right buyers. Every item is a cold start; that's the problem.

• Power-seller tooling. Design and launch the management tools that high-frequency sellers and veteran hobbyists actually need. Watch what they do in spreadsheets today, then delete the spreadsheet.

• The whole experience. Backend bid resolution through the responsive UI where the action happens. You own the schema change and the screen it ripples out to.

• The bar. Mentor the team and set the standard for code quality, reliability, and performance.

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:

• Ship instant valuation into the consignor flow — take an Alt Value, a card's condition and provenance language, and recent comps, and produce an upfront liquidity offer a seller can accept in one tap. This is the flagship AI feature on this team, and it is user-facing

• Use vision and language models to enrich listings at scale: parse condition notes, extract attributes from listing photos and descriptions, and turn a messy long tail of one-of-one items into structured data a recommender can actually use

• Build a load-and-concurrency harness you can talk to — generate the closing-seconds bid storm, replay it against a branch, and get back where the write path bent, without spending two days wiring a load test

• Stand up an agent over auction telemetry that watches close windows and flags anomalies — bid latency creeping, a seller's listings underperforming their comps — before a power seller emails us about it

• Put an MCP server over listing, bid, and pricing history so "why did this lot close low" is a sentence, not another one-off query

• Use Claude Code or Cursor as the default way you work through a refactor or a migration, not as autocomplete

If you've built agents, wired up connectors, written skills or MCP servers, or shipped internal tooling your team actually depends on — lead with that. Name the artifact, not the tool.

What You Bring:

• 5+ years building and scaling complex applications — Python, Postgres, AWS or comparable cloud infrastructure.

• Modern frontend mastery. Deep experience with React, TypeScript, and building high-performance real-time UIs. Real-time is the operative word: this is not a CRUD screen.

• Reliability under pressure. A track record of building systems that stay up when the stakes and the traffic are highest. You've been paged during the worst possible ten minutes.

• AI pragmatism. You've taken LLMs or computer vision models and turned them into practical, user-facing features that solved a real business problem. Not a demo.

• Product instincts. You don't build what's on the ticket. You understand the collector mindset and build things that delight them — and you can explain the why behind past work before you explain the how.

• High agency. You thrive where you're expected to find the highest-leverage work and go execute it without a hand-holding manual.

Bonus: experience with personalization engines, recommendation systems, or AI/ML integrations. Startup experience. You collect, or you have a view on where this market is going.

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, and try our selling feature. Every round assumes you've used the product, and we expect your point of view to sharpen as you go. For this role, actually sit through the end of a live auction. Notice what the UI tells you and what it doesn't.

1. Recruiter screen — 25 minutes, Google Meet. Come ready to talk about the metric you own today and how you're performing against it, why Alt specifically, and how you're actually using AI. We'll align on comp and answer your questions.

2. Hiring manager — 45 minutes, Google Meet. Be ready to go deep on a project you owned end to end — starting with the problem it existed to solve, then the design, then what was yours versus the team's, then the outcome.

3. Technical screen — 60 minutes. A hands-on working session (Live Coder pad)

4. System design — 60 minutes.

5. Culture Interview,- 30 minutes.

6. Leore, our founder and CEO — 30 minutes Everyone who joins Alt meets Leore. Come with a point of view on where you'd take auctions first.

7. Reference checks — 15 minutes with a former manager(s)

Compensation: $200,000 - $220,000 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