New offer - be the first one to apply!
June 18, 2026
Mid • Hybrid
14,600 - 20,825 PLN/mo
Warsaw, Poland
Allegro is home to 2,500+ tech experts, but our teams ensure the physical reality of e-commerce runs flawlessly. We are looking for engineers who want to solve large-scale challenges in areas critical to the shopping journey and logistics platform — from delivery selection to systems powering order fulfillment at massive scale.
This team focuses on the massive-scale ecosystem behind order fulfillment, ensuring business continuity and total platform independence by building robust and scalable systems capable of absorbing total traffic volume. They evolve system capacity and traffic routing management, expand a network of external logistics partners, and refactor architecture to process hundreds of millions of records, predict system load, and optimize volume distribution. The team also defines and executes a unified, cross-organizational location intelligence strategy to standardize geo-data and optimize addressing at scale.
This team works on a critical part of the shopping journey: delivery selection. They build solutions handling around 40k requests per second, deploy to production multiple times a day, and treat every change as an independent increment. They focus on code quality, automated testing, reliability, knowledge sharing, continuous development, and use AI in daily work to support feature development.
We are looking for a Software Engineer 2 with a strong background in back-end programming (Kotlin) and software architecture, ready to lead structural improvements in high-volume data processing software and location intelligence. You will take ownership of complex systems where your decisions directly impact operational efficiency.
Work within a self-service ecosystem using tools such as Kubernetes, Docker, Consul, GitHub, and GitHub Actions. Contribute to an environment with over 2000 microservices, an open-source data bus (Hermes) handling 300K+ rps, a Service Mesh with 1M+ rps, tens of petabytes of data, and production-used machine learning. Use modern AI tools to automate repetitive tasks and enhance service development.