Staff Backend Engineer — AI-Driven Food Ops Systems

HelloFresh Group; Toronto; Híbrido; CAD 180.000 - 215.000; Tempo integral

Benefícios oferecidos por esta vaga

Box Discounts

Health & Wellness benefits

Vacation & PTO

Parental leave top-up

Resumo da vaga

HelloFresh is hiring a Staff Backend Engineer to join the Ingredient to Product tribe in Toronto. This role blends Food Systems and Backend Engineering to translate business needs into scalable production systems and solutions.

You will work across squads to raise the bar and deliver value to customers with strong Python and distributed systems expertise. You will own backend-heavy problems, design robust services, and operate them in production with observability and AI-assisted tooling.

Qualificações

• Strong Python (and Golang) background with production distributed systems experience.
• Hands-on experience with AI tooling and AI agents in daily workflows.
• Ownership mindset with a bias to ship and finish tasks.
• Product sense and ability to back decisions with data and user feedback.

Responsabilidades

• Design, build, and own scalable infrastructure for menu operations across services.
• Bridge Food Systems business needs with backend engineering to create scalable solutions.
• Lead backend-heavy product problems and ensure reliable, observable services at scale.
• Collaborate beyond specialization when needed to solve complex issues.
• Operate and monitor production systems; ship iteratively as learning continues.

Conhecimentos

Python

Golang

AI tooling

Distributed systems

Ferramentas

Claude Code

Cursor

Copilot

Descrição da vaga

HelloFresh is hiring a Staff Backend Engineer to join the Ingredient to Product tribe in Toronto. This role blends Food Systems and Backend Engineering to translate business needs into scalable production systems and solutions.

You will work across squads to raise the bar and deliver value to customers with strong Python and distributed systems expertise. You will own backend-heavy problems, design robust services, and operate them in production with observability and AI-assisted tooling.