Desarrollador Full Stack

Currently, we have a Microservice Cloud-based SaaS using React, Python, Java, MongoDB, and cloud infrastructure provided by OVH and Vercel. As the project evolves rapidly, we are looking forward to welcoming a skilled Full Stack Developer to our awesome team & exciting project.

About the Role We are looking for a Full Stack developer with genuine experience in developing and integrating AI into products.

Responsibilities

• Develop and maintain high-quality, scalable, and efficient code for both frontend and backend.

• Contribute to the development of our Microservice Cloud-based software using React, Python, Java, and MongoDB.

• Collaborate with cross-functional teams to define, design, and ship new features.

• Contribute to the development of new AI-related features in our SaaS solutions.

• Ensure the performance, quality, and responsiveness of applications.

• Identify and correct bottlenecks and fix bugs.

• Help maintain code quality, organization, and automation., * Vercel

• FastAPI

• Spring Boot

• React, NextJS, and TypeScript

• MongoDB, PostgreSQL

• Hexagonal architecture (Frontend and Backend)

• Scrum

• SOLID principles

• Microservices

• SonarCloud

• Atlassian (Jira, Bitbucket, Confluence)

• CI/CD with Bitbucket Pipelines, Jornada

• Más de 5 años Experiencia

• Indefinido Tipo contrato

• React Python Java Microservices

Ofertas de empleo similares

Fullstack Developer React/Node/GraphQL - HAYS Fullstack Developer (JavaScript/PHP) - HAYS Programador/a Front React - CAS TRAINING

Frontend:

• 5+ years' experience as a Front-End Developer with relevant experience using React.
• Mastery of HTML/CSS/modern JavaScript.
• Expertise in responsive development, frontend performance, and state management.
• Experience with task runners (Webpack/Vite) and testing frameworks (Jest).
• Proficiency in TypeScript and applying best practices in version control software (Bitbucket).

Backend:

• 5+ years' experience as a Back-End Developer.
• Proficiency in Java or Python (both is a plus).
• Experience with web frameworks (Spring Boot, Django, FastAPI).
• Knowledge of testing frameworks (Mockito, Pytest).
• Understanding of high-level architecture such as hexagonal architecture or MVC.
• Experience with relational and non-relational databases (PostgreSQL, MongoDB).

IA:

• Integration of LLM APIs (Gemini, OpenAI, Anthropic) into real-world backend services.
• RAG implemented and in production: chunking, embeddings, vector database and retrieval.
• Managing context windows in real-world scenarios.
• A clear distinction between prompt engineering, RAG and fine-tuning.
• Observability of LLMs in production using LangSmith, Langfuse or similar tools.
• Experience in evaluating and measuring the quality of AI systems.
• Familiarity with AI orchestration frameworks ( LangChain, LlamaIndex or similar), applied to data automation workflows and not just to chatbots or conversational interfaces.
• Proven experience in training and deploying ML models in production (not just for experimentation), with end-to-end pipelines from data ingestion to serving.
• Practical application of time series models for demand forecasting, or temporal transformer models.
• Proficiency in MLOps tools: designing pipelines using MLflow, Airflow or similar; model versioning; monitoring drift in production.

General:

• Languages: Spanish is required. English level (B2)