Amazon-quality product recommendations for any e-commerce store

Lead JavaScript Engineer

3+ years

Amazon-quality product recommendations for any e-commerce store.

Amazon has the best product recommendations. They use their historic sales data to create these recommendations. The problem though is that other e-commerce stores lack enough sales training data to do the same.

We've solved this problem. The algorithm increases overall e-commerce revenue by 4-6% for any store without needing any sales data at all.

About the role

Skills: JavaScript

Do you want to join a fast-paced startup and work on the bleeding edge of what's technically possible in a browser? We are looking for a Senior Javascript/Full-Stack Engineer with 5+ years of experience.

What you will be building:

Self-contained JavaScript plugins that add's AI-functionality to e-commerce websites.

There's an art to writing JavaScript-embeddable scripts that can plug into any website. They must adapt easily to unknown host environments, coexist with other applications, and manage the tricky security vulnerabilities you get when code and asset files are served from remote web addresses.

We need someone who we can count on to:

Own: Tooling and infrastructure to provide and easily maintain 100's of 5-minute copy/paste JavaScript integrations and scrapers.

Teach: What's possible and what's not possible? Tradeoffs between ease of integration and page performance. How to build a system that can withstand unforeseen circumstances where we don't have much control.

Learn: How to hack into popular SPA-frameworks, architect integrations resilient to minor style changes, optimize loading speeds, and build tooling that other individuals can work efficiently with.

Improve: Efficiency and robustness of integrations operating inside evolving environments.

We expect you to know:

  • JavaScript (TypeScript), CSS and HTML

Nice to have

  • Tracking and analytics
  • Inner workings of how popular SPA-frameworks function
  • Docker
  • Node.js
  • Cloud computing (AWS, GCP or Azure)
  • Puppeteer

Within 1 month we expect you to:

  • Understand the ins and outs of why we're approaching our integrations as we do.
  • Have talked with existing clients to understand their pain points.
  • Read the book "Third Party JavaScript",
  • Get to know our Frontend Integration Engineer and how they're using our existing framework at the moment.
  • Build out 3-5 integrations yourself to get a sense of how our existing frameworks work.

Within 3 months we expect you to:

  • Build a functional low-code point-and-click interface that sets up tracking and analytics automatically for most sites (~80-90% coverage).
  • Build a functional low-code WYSIWYG-interface where one can reliably style and inject widgets into almost any site (~80-90% coverage).
  • Make major improvements on top of existing framework that scrape high amounts of e-commerce data every day from multiple sites. Highly resilient against anti-bot and style changes.
  • Framework for visual automated tests that can verify that our integrations are working as expected.
  • Mentor and onboard 2-3 new frontend integration engineers into the framework.

Within 6 months we expect you to:

  • Be the development lead of a team of 1-2 other developers working the same project.
  • Built out framework to support a higher variety of widget types and functionality (search, category listing, pop ups, e.t.c).
  • Increased coverage of framework to ~95% of all websites.
  • Increased efficiency of internal tools to sustain a low amount of frontend integration engineers while exponentially increasing the amount of customers joining our platform.
  • Refining software to make as much as possible self-serve.

Within 12 months we expect you to:

  • Build out sufficient amount of tooling and support to be able to provide a no-code self-serve solution to integrate with, agnostic to which e-commerce platform it's using.
  • Start exploring ways to increase our product offering and upsell customers to not only show product recommendations on e-commerce pages.

Our selection process is continuous and we may move forward with candidates on an ongoing basis. If you have any further questions about the role, please contact [email protected].


  1. Scrape e-commerce stores to fetch their product data (using Kubernetes (Argo), Puppeteer & Tor for IP-rotation)
  2. Fine-tune & iterate on the recommender system (hybrid model based on content fetched from specialized ConvNets and collaborative filtering)
  3. Tooling to auto-generate JS-snippets that can inject our product recommendations widget and collect analytics of how it performs (Chrome Extensions, Babel and styling with CSS)

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