Backend Engineer to join an international technology project focused on building an intelligent platform that combines
Python backend development, APIs, LLM-based agentic workflows and large-scale data processing
.
Location
Spain
Work model
100% Remote
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
.
What are we looking for?
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.