Backend Software Engineer – AI Commerce Platform

Python | GCP | Distributed Systems | AI

Fast Simon is building the AI systems that decide what millions of ecommerce shoppers discover, see, and buy.

Work on real time search, personalization, recommendations, AI Shopping Agents, and large scale distributed systems, all running in production for thousands of online stores.

We are looking for exceptional backend engineers, from outstanding recent graduates to experienced developers. Ability, curiosity, and what you have built matter more to us than years on your CV.

WHAT MAKES THE WORK INTERESTING?

A shopper searches: “Black dress for a September wedding in Italy, elegant but not too formal, under $300.”. Behind a simple request like this are some of the problems our engineers work on:

• Understanding natural language and shopper intent

• Searching and ranking large product catalogs in real time

• Personalizing results for an individual shopper

• Combining AI decisions with inventory, merchandising, and brand constraints

• Learning continuously from shopper behavior

• Keeping response times extremely fast

• Using A/B testing to determine whether a new experience actually increases merchant revenue

And that is only one part of the platform.

WHAT YOU COULD WORK ON

• AI Shopping Agents that turn shopping into a conversation

• Real time 1:1 personalization across search, collections, and recommendations

• Search, ranking, and relevance systems

• Recommendation and Complete the Look algorithms

• Visual similarity and visual product discovery

• High volume behavioral event processing

• Experimentation and A/B testing infrastructure

• Distributed cloud services where latency, reliability, and cost matter

OUR BACKEND

• Python

• Google Cloud Platform

• Kubernetes and Cloud Run

• Redis and distributed caching

• Event driven services and data pipelines

• APIs serving live ecommerce experiences

• Extensive monitoring, testing, and production observability

We also use AI development tools, including Claude Code, as part of our workflow. We want engineers who know how to use AI to move faster while still understanding the architecture, making sound engineering decisions, verifying the result, and taking responsibility for production quality.

WHO WE ARE LOOKING FOR?

There is no perfect number of years. We want engineers who can demonstrate strong software engineering ability through what they have built, solved, or learned.

That could mean:

• You have owned significant production backend systems

• You built an ambitious university or personal project

• You contributed meaningfully to open source

• You gained deep technical experience in a military technology or intelligence unit

• You learn unusually quickly and can demonstrate strong computer science and engineering fundamentals

You should be comfortable with algorithms, data structures, APIs, databases, concurrency, debugging, and reasoning about complex systems.

More importantly, you should be curious about how things actually work and willing to investigate beyond the first plausible answer.

You should be able to work independently without working in isolation: ask for help early, share knowledge, give and receive direct feedback, and help the team reach a better result.

WHY FAST SIMON?

IMPACT: What you build reaches real shoppers and affects real merchant revenue.

OWNERSHIP: You will own meaningful production problems early, with the support and authority needed to carry them through.

BREADTH: In one company, you can work across search, AI, personalization, recommendations, distributed systems, data, and ecommerce.

SPEED: The distance between an idea, production, and learning from actual users is short.

AI AI is not a side project here. It is part of both the products we build and the way we build software.

LEARNING: You will work closely with experienced engineers while being expected to think independently, contribute ideas from the beginning, and help raise the standard for the whole team.

Do not rule yourself out because you lack a particular degree, background, or number of years. We evaluate technical depth, judgment, learning speed, and demonstrated impact, not years of experience alone.

HOW TO APPLY?

Along with your CV, tell us about one technically difficult thing you have built.

It can be from work, university, the military, open source, or something you built simply because you wanted to.

Tell us what was hard, what you personally contributed, how you worked with others, and what you would do differently today.

After pasting, you can optionally select each ALL CAPS section title in LinkedIn and click B. The • bullets themselves should survive the paste as shown.