> Markdown version of [/jobs/ext/2811538-backend-engineer-python-fastapi-llm-pipelines](https://www.wearedevelopers.com/jobs/ext/2811538-backend-engineer-python-fastapi-llm-pipelines). 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 - Python / FastAPI / LLM Pipelines - **Company:** Provincia De Valencia - **Location:** Valencia, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Big Data, Data Transformation, Python (Programming Language), PostgreSQL, Search Technologies, SQLAlchemy, Systems Integration, Extensible Markup Language (XML), Large Language Models, Backend, AWS ECS, Fastapi, Pandas, Pytest, Containerization, AWS Aurora, AWS Fargate, Api Design, Restful APIs, Docker, Service Stack - **Published:** September 9, 2026 - **Apply:** https://www.adzuna.es/contact-us.html ## About the Role + Strong professional experience with Python . + Solid experience developing APIs with FastAPI . + Experience with Pydantic, async Python and typed backend development . + Experience with SQLAlchemy and PostgreSQL . + Hands-on experience developing LLM applications using LangGraph and/or LangChain . + Experience integrating OpenAI or Azure OpenAI APIs . + Knowledge of RAG, embeddings, vector search and structured LLM outputs . + Experience implementing techniques to reduce hallucinations and improve LLM output quality. + Experience processing structured or semi-structured datasets. + Knowledge of Docker and AWS cloud services . + Experience with automated testing using pytest . + Experience with XML processing is highly valued. + Experience with AWS Aurora, ECS/Fargate or RDS Data API is a plus. + Good professional English communication skills. Technology Stack Python · FastAPI · LangGraph · LangChain · Azure OpenAI · RAG · FAISS · Pydantic · SQLAlchemy · PostgreSQL · AWS Aurora · Docker · ECS/Fargate · pandas · XML · pytest If you enjoy working at the intersection of backend engineering, generative AI and cloud-based data processing , we would love to hear from you. ## Description Environment: International team ️ English: Good professional working proficiency required What will you be working on? You will help build and operate the Python backend behind an AI-powered platform used to process, compare, update and evaluate complex technical content. Your responsibilities will include: + Designing and maintaining REST APIs using Python and FastAPI . + Developing typed API schemas with Pydantic and strong typing practices. + Building asynchronous backend components and secure endpoints. + Developing agentic AI pipelines using LangGraph and LangChain . + Implementing workflows for content discovery, matching, editing, validation and evaluation. + Integrating Azure OpenAI models using structured outputs and function/tool calling. + Developing RAG-based solutions using embeddings and FAISS . + Implementing grounding, provenance and hallucination-control mechanisms. + Processing engineering datasets and large structured XML documents. + Performing data transformations using pandas and openpyxl . + Developing database integrations using SQLAlchemy 2.x, PostgreSQL and AWS Aurora . + Containerizing and deploying backend workloads using Docker and AWS ECS/Fargate . + Working with AWS services such as ECR, Secrets Manager, RDS and SSO . + Maintaining automated testing practices using pytest . ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [pytest: Simple, rapid and fun testing with Python](https://www.wearedevelopers.com/videos/213-pytest-simple-rapid-and-fun-testing-with-python) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Accelerating GenAI Development: Harnessing Astra DB Vector Store and Langflow for LLM-Powered Apps](https://www.wearedevelopers.com/videos/966-accelerating-genai-development-harnessing-astra-db-vector-store-and-langflow-for-llm-powered-apps) ## Related Articles - [The 7 Most Popular Backend Frameworks for Developers](https://www.wearedevelopers.com/magazine/403-the-7-most-popular-backend-frameworks-for-developers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)