> Markdown version of [/jobs/ext/3044131-backend-engineer-product-team](https://www.wearedevelopers.com/jobs/ext/3044131-backend-engineer-product-team). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Backend Engineer (Product Team) - **Company:** Leovegas Group - **Location:** Barcelona, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, App Store (IOS), Unit Testing, Big Data, Software as a Service, Relational Databases, Database Queries, DevOps, Distributed Systems, Python (Programming Language), PostgreSQL, Enterprise Messaging Systems, MongoDB, MySQL, NoSQL, RabbitMQ, SQLAlchemy, Systems Integration, Strategies of Testing, Web Services, Workflow Management Systems, Data Processing, Cloud Platform System, Large Language Models, Backend, Fastapi, Pytest, Apache Kafka, Text Summarization, Data Pipelines - **Published:** September 24, 2026 - **Apply:** https://www.adzuna.es/contact-us.html ## About the Role 5+ years of professional experience in backend software development. 3+ years of experience working with asynchronous Python (asyncio). Strong proficiency in FastAPI for building scalable API services. Solid experience with relational databases such as MySQL or PostgreSQL, including strong SQL skills. Experience working with ORM frameworks, preferably SQLAlchemy. Hands-on experience with NoSQL databases such as MongoDB. Experience with messaging systems such as RabbitMQ or Kafka. Strong understanding of unit testing practices, particularly using Pytest. Experience working in distributed systems and scalable backend architectures. Upper-intermediate or higher level of English proficiency. Strong problem-solving skills, attention to detail, and ability to work in a fast-paced product environment. Nice to have: experience with NLP, LLM-based systems, or AI-powered features. Nice to have: experience building or integrating LLM applications (RAG, AI assistants). Nice to have: familiarity with vector databases and modern AI storage systems. Nice to have: experience with data pipelines and orchestration tools such as Airflow or Prefect. Nice to have: exposure to AWS or other cloud environments. Nice to have: experience in research and development (R&D) or experimental engineering projects. ## Description As a Senior Backend Engineer, you will play a key role in building and scaling a global SaaS platform that helps businesses manage app performance, user feedback, and marketplace analytics. You will contribute to the development of high-impact backend services that process large volumes of data from app stores and transform them into actionable insights. Working in a fully remote, product-driven environment, you will collaborate closely with cross-functional teams to design robust, scalable, and secure systems. This role offers the opportunity to work on complex engineering challenges, including automation, data processing, and AI-driven features such as semantic analysis and summarization. You will help shape the architecture of a fast-growing platform while improving performance, reliability, and developer experience. Accountabilities Develop, maintain, and optimize backend services that power core product features related to app ratings, reviews, and performance analytics. Design and implement systems for automating user interactions with customer reviews, including tagging, response workflows, and reporting capabilities. Build and enhance data processing pipelines to generate insights from large-scale user feedback and app store data. Contribute to AI-powered product capabilities, including semantic analysis, text summarization, and intelligent automation features. Support and improve internal and public APIs connected to core platform data entities. Design scalable, secure, testable, and well-documented backend architectures. Collaborate with engineering peers to improve system-wide architecture and ensure consistency across services. Work with and modernize legacy services while ensuring stability and performance. Partner with platform and DevOps teams to ensure smooth deployments and reliable system operations across environments. Apply engineering best practices, coding standards, and testing strategies to maintain high-quality software delivery.