Senior Backend Engineer, Shopping Agents

Sage AI Labs

Berlin

Remote

EUR 90.000 - 130.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

Sage AI Labs in Berlin is building AI-driven shopping agents that transact on the open web. We’re looking for a Senior Backend Engineer to own architecture, code, deployment, and on-call for scalable checkout systems.

You’ll work with the CTO to secure delivery at real scale, ingest data from hundreds of sources, and optimize search, ranking, and reliability in a rapidly evolving ecommerce environment.

Qualifikationen

  • 5+ years of backend and infrastructure experience.
  • Experience owning production systems end to end.
  • Strong Python programming skills.

Aufgaben

  • Own checkout agents and live at-scale deployments.
  • Handle ingestion from hundreds of sources and scale infra.
  • Develop search, ranking, and caching for a changing catalog.

Kenntnisse

Python
Backend development
Observability
DevOps
Distributed systems

Tools

Databases
Monitoring tools

Jobbeschreibung

Senior Backend Engineer, Shopping Agents

Sage AI Labs · Berlin · Full-time · [Remote]

About us

Sage AI Labs is building the infrastructure that lets AI agents transact on the open web. It is one of the few genuinely unsolved problems left in commerce, and whoever solves it sets the defaults everyone else builds on top of.

The company was founded by Sebastian Thrun (founder of Google X and Waymo, Udacity) and is backed by leading venture and strategic investors.

About the role

We build agents that shop for you. They find products across the open web and complete the purchase end to end. Real carts, real payments, and real systems built to stop them.

You would own that. Architecture, code, deploys, monitoring, and on-call for systems that transact around the clock, working directly with our CTO.

What you'll own

Our checkout agents. Frontier-model computer-use agents driving live checkouts at scale, plus the machinery that keeps them standing when the ground moves. Every retailer breaks differently and they change without warning. Your job is to make failure rare and recovery automatic.

Ingestion at scale. Take product ingestion from hundreds of sources to thousands. The answer is not more hand-written code. It is infrastructure that generates, validates, and monitors itself.

Search and ranking. Embedding-based retrieval, LLM query understanding, reranking, and caching, across a catalog that never stops changing.

What we're looking for
  • 5+ years building backend and infrastructure systems, with strong Python

  • You have owned production systems end to end: deploys, databases, observability, and the pager. You have been the person who got paged, and you fixed the class of problem rather than the incident

  • You like adversarial problems. Systems where something on the other side is actively working against you

  • You can move without a finished spec. We are small, and the roadmap changes when the market does

Nice to have
  • Built AI-first products or LLM-based agents in production, not just in a prototype

  • Working knowledge of classic ML and deep learning, enough to reason about retrieval and ranking rather than only calling an API

  • Background in e-commerce, payments, or fraud and risk infrastructure

Why this role

Very few engineers get to own a category-defining system while the category is still being defined. This is one of those seats, at the point where it still counts as early. A year from now this problem will have a standard answer and someone will have written it. We intend for that to be us.

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