Job Description BUSCAMOS: Senior Python Cloud Engineer (Azure)
Knowledge Requirements for New Developers
1. Core Concepts
- RAG (Retrieval-Augmented Generation) — the entire system is a RAG chatbot pipeline;
understanding howretrieval, chunking, embedding, and generation work together is essential
- Microservice architecture — the system is composed of ~8 independent services communicating via HTTP and message queues
2. Python
- Python 3.11 (hard requirement for Azure Functions consumption plan)
- Flask — backend, chunker, converter, connector, and image processor are all Flask apps
- FastAPI — the evaluator service uses FastAPI with async support
- Streamlit — the admin UI is built with Streamlit
- Poetry — dependency management across all services
- uv — used as an alternative Python package manager (Azure Functions)
3. Azure Cloud Services
- Azure Blob Storage — document storage, evaluation results, crawled data
- Azure AI Search (Cognitive Search) — vector/hybrid search index for document chunks
- Azure OpenAI — LLM inference (GPT-4, embeddings via text-embedding-3-large)
- Azure Document Intelligence (Form Recognizer) — PDF/document parsing and OCR
- Azure Container Apps — production hosting for all microservices
- Azure Container Registry (ACR) — Docker image storage and build
- Azure Functions — queue-triggered indexing pipeline (blob → convert → chunk → embed → index)
- Azure Queue Storage — async messaging between services (indexing queue, poison queue)
- Azure EntraID — authentication and role-based access control
- Azure Application Insights — telemetry and logging
- Azure CLI — deployment, ACR interactions, Container App updates
4. Docker & Containers
- Docker — every service has a Dockerfile;
local developmentand production both use containers
- Building, running, and debugging containerized Python services
5. Data Sources & Crawling
- SharePoint Online — document library crawling with auth
- Confluence — page and page-tree scraping with PATs
- Web crawling — generic website crawling with depth control
6. AI / ML Evaluation
- RAGAs framework — evaluation metrics (faithfulness, answer relevance, context precision/recall)
- LLM-as-judge — using GPT-4 to score answer quality
- Locust — load/performance testing framework for the RAG API
7. Observability
- LangFuse — LLM observability and tracing platform
- Application Insights — Azure-native telemetry
8. Development Tools
- VS Code — launch configurations, debug configs, tasks
- Azurite — local Azure Storage emulator (queues, blobs)
- Azure Functions Core Tools — local Azure Functions runtime
- Git — branching model: dev/ → dev/featureX → PR to main
Idioma
■ Español
■ Inglés C1
·
OFRECEMOS:
· Contrato en modalidad Freelance Full time
· Oferta económica: 250€/290€ jornada + IVA (según experiencia aportada)
· Proyecto de larga duración
· Localización: España (Teletrabajo 100% )