Summary
✨ AI‑Generated
A technology team is hiring a Python Backend Developer to design and maintain event-driven services for a high-growth platform. The role includes building reliable APIs, managing message queues, containerization, and contributing to architectural decisions.
Highlights
Opportunity to build scalable backend systems supporting advanced technology initiatives, with focus on reliability, automation, and modern architecture.
Description
About the project
We're looking for a Backend Developer Python to build and evolve the internal platform that supports the AI team of a leading client in the renewable energy sector.
It's an event-driven platform that needs to handle variable load, recover from failures without manual intervention, and scale at the pace demanded by a fast-growing AI team.
What you'll do
Design, build, and maintain Python backend services within an event-driven architecture.Design and manage queues and consumers (RabbitMQ): load balancing across consumers, retry and failure-recovery strategies, handling messages that can't be processed.Containerize services with Docker and take part in deployment infrastructure decisions.Work directly alongside the platform's AI team, understanding their consumption needs and integrating their work into the backend.Contribute to architecture decisions: integrations between microservices, dependency management, and packaging.
Requirements (must-have)
Solid Python experience in production environments, with at least one of these frameworks: FastAPI, Django, or Flask (experience with async frameworks is especially valued).Real experience building or maintaining event-driven architectures / distributed systems with message queues (RabbitMQ, Kafka, or similar).Ability to explain, with real judgment, how consumer failures are handled: what happens when a message can't be processed, how to prevent it from blocking the queue and affecting the rest of the system, and what retry/discard strategies are applied.Experience creating your own Dockerfiles and working with Docker Compose; solid understanding of what a Docker layer is and how it works.Experience working with microservices and their integrations (APIs, queues, events).Comfortable with Python dependency management (pip, PyPI; experience with uv is a plus).
Nice-to-have
Experience with Apache Airflow for workflow/pipeline orchestration.Integrating uv inside a Dockerfile.Experience with AI agents or agentic systems.Regular use of AI as part of your own development workflow (Cursor, Claude Code) — not just code generation, but critical review and validation of generated code.Prior experience in energy or industrial sector projects.
