Staff Software Engineer

HelloFresh is a global technology organization with over 1000 people building digital products behind their end-to-end food experience, including meal kits, ready-to-eat meals, pet food, and premium meat & seafood. HelloTech is organized into autonomous, cross-functional alliances, each owning a specific domain. The Shopping AI & Search squad, part of the Shopping Journey tribe within the Consumer Alliance, focuses on building unified AI Assistant experiences for customers to enhance the shopping journey.

• 8+ years of backend engineering experience with expertise in distributed systems, microservices, and event-driven architecture (using Kafka, RabbitMQ, or AWS SQS/SNS).
• Strong hands-on proficiency in Go or other modern backend languages (Java, Kotlin, Python, TypeScript, Node.js), with willingness to work in Go.
• Practical experience integrating LLMs or AI services into production systems via APIs/SDKs, understanding latency, cost, and non-determinism.
• Daily hands-on use of AI coding tools (Claude Code, Cursor, Copilot) with practical understanding of their usage.
• Solid understanding of modern cloud infrastructure (AWS, Kubernetes) and observability practices.
• Ability to translate ambiguous product problems (search relevance, recommendation quality, conversational UX) into clear technical roadmaps.
• Collaborative and low-ego problem-solving approach, strong technical judgment, and mentoring skills.
• Excellent communication skills working with senior stakeholders and international teams.

• Lead the technical architecture for unified AI Assistant experiences including conversational and personalized search and proactive in-app recommendations.
• Own end-to-end technical decisions integrating LLM-powered capabilities into customer-facing systems considering quality, latency, and cost.
• Act as the technical bridge between Shopping AI & Search, neighboring squads, and stakeholders to maintain coherent architecture.
• Define and drive engineering best practices for AI-powered systems including observability, graceful degradation, and probabilistic testing strategies.
• Provide technical leadership through architecture reviews, design discussions, and mentoring.
• Use AI coding tools (e.g., Claude Code, Cursor) as standard practice and help the team adopt AI-assisted engineering.
• Shape the technical roadmap by identifying and addressing architectural bottlenecks early.

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