Senior Backend Engineer - Menu Personalization

Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month. Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.

• Long-term (5+ yrs) work experience in backend engineering, with a strong focus on building distributed systems and microservices.
• Deep proficiency in Golang and experience with its ecosystem in a production environment.
• Comfortable reading, understanding, and contributing to Python codebases; willing and able to familiarize with Python/FastAPI services and collaborate with Data Scientists.
• Proven track record with event-driven architectures and handling large-scale, heterogeneous datasets.
• Hands-on experience with cloud infrastructure, container orchestration (Docker), and robust CI/CD pipelines.
• Strong foundation in software development best practices, including TDD, clean code, and Git.
• Experience leveraging Generative AI tools (e.g., Claude, GitHub Copilot) to accelerate development and improve code quality.
• Exceptional ability to translate technical architecture into business value for non-technical stakeholders and product partners.

Architect & Build:

• Deliver the core of our personalization engine by engineering high-availability Golang microservices that power real-time recommendations.
• Build and optimize Python/FastAPI services that rank recipes using ML embeddings and sophisticated multi-objective optimization algorithms.

ML Operationalization:

• Partner closely with Data Scientists to translate complex statistical solutions and ML models into production-ready services.

System Evolution:

• Shape the future of our personalization platform by re-architecting legacy components into scalable, event-driven systems that can handle millions of requests globally.

Operational Excellence:

• Manage the full lifecycle of your services—from experimentation and local development to deployment and monitoring in production.

Experimentation Support:

• Design and implement the backend infrastructure required to execute A/B tests and measure the impact of new recommendation strategies.

Tech Stack Mastery:

• Work with state-of-the-art technologies including Kafka, Redis, SQS, FastAPI, Kubernetes, Docker, and PostgreSQL.
• Provide knowledge sharing and technical guidance to other engineering contributors through code reviews and architectural alignment.