Staff Backend Product Engineer, Operations Technology (all genders)

We're looking for a Staff Backend Engineer to join our Ingredient to Product tribe at HelloFresh. This is a high-impact individual contributor role sitting at the intersection of Food Systems and Backend Engineering — you'll be the technical bridge that identifies business and technical gaps and works with business ...

You'll work across squads within the Food Systems alliance, partnering closely with Backend Engineers to ensure E2E menu operational efficiencies are met, raise the technical bar, and accelerate the tribe's ability to deliver value to our customers.

At HelloFresh we are moving away from a model where software developers just execute tickets toward one where product engineers are trusted to own customer problems. A Product Engineer takes a problem, forms a point of view, validates it with customers and data, and ships it using AI as a force multiplier.

We're looking for a Staff Backend Engineer to join our Ingredient to Product tribe at HelloFresh. This is a high-impact individual contributor role sitting at the intersection of Food Systems  and Backend Engineering — you'll be the technical bridge that identifies business and technical gaps and works with business leads to turn requirements into scalable production systems and solutions.
You'll work across squads within the Food Systems alliance, partnering closely with Backend Engineers to ensure E2E menu operational efficiencies are met, raise the technical bar, and accelerate the tribe's ability to deliver value to our customers.
Design, build, and own robust, scalable infrastructure for menu operations and be a key driver to ensure a successful xPS migration in the US market.
Act as the technical bridge between Food Systems business leads and Backend Engineering teams within the Ingredient to Product tribe — translating needs into scalable engineering solutions
Take the technical lead on backend-heavy product problems, designing, building and operating the services and systems needed to deliver them reliably at scale.
Work beyond your specialization when the problem demands it. Your specialization is your anchor, not your boundary.
Operate what you build. You instrument, monitor, and improve your systems in production. Shipping is the beginning of the learning cycle, not the end.

Hands-on experience working with AI tooling (e.g., Claude Code, Cursor, Copilot) beyond casual experimentation. You use AI agents every day. You have a practical sense of how the context you provide to AI tools shapes output quality, and how to set boundaries on AI-generated work.
Strong fluency in Python (Golang is a plus) and hands on experience building distributed systems in production: event-driven and asynchronous flows, clear service contracts, and designing for partial failure. You operate what you build, including its observability and data layer.
You take full ownership. You have a bias to ship. You finish the last twenty percent. 
You have product sense and are opinionated about what should be built and why, and you can back that opinion with data and user evidence.