Desarrollador de Python

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.