Senior Java

Hace 1 día

Madrid, Community of Madrid, España Wizeline Jornada completa

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Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact. With the right people and the right ideas, there’s no limit to what we can achieve. Sounds awesome, right? Now, let's make sure you're a good fit for the role: Key Responsibilities

About the Role

We are looking for a

Java Developer

with a foundation in core Java engineering and an eagerness to build modern, AI-powered applications. In this role, you will work on scaling backend microservices while leveraging emerging AI frameworks to integrate Large Language Models (LLMs), RAG (Retrieval-Augmented Generation) pipelines, and intelligent automation into our enterprise platform. Key Responsibilities

Backend Engineering:

Design, build, and maintain scalable RESTful APIs and microservices using Java and Spring Boot. AI & LLM Integration:

Connect backend systems with modern LLM provider APIs (OpenAI, Anthropic, Ollama, Hugging Face) using Java AI libraries like

LangChain4j

or

Spring AI . Vector Search & RAG:

Assist in integrating vector databases (e.g., pgvector, Qdrant, Pinecone, or Milvus) to support intelligent search and contextual knowledge retrieval. Collaboration & Testing:

Write clean, testable code (JUnit/Mockito) and collaborate with product managers, frontend engineers, and DevOps to ship AI-enhanced features. Qualifications & Skills

7 years

of hands-on software development experience with

Java 17+ . Strong experience with

Spring Boot , REST API design, and microservice architectures. Experience with relational databases ( PostgreSQL ,

MySQL ) and ORM tools ( Hibernate/JPA ). Familiarity with containerization ( Docker ) and modern CI/CD workflows. Basic AI / LLM Knowledge:

Understanding of core LLM concepts (prompts, context windows, tokens, embeddings, and temperature). Hands-on experience or coursework integrating REST-based AI APIs (e.g., OpenAI, Anthropic, Azure OpenAI). Familiarity with at least one Java AI framework ( LangChain4j

or

Spring AI ) or open-source vector stores. Basic understanding of

RAG (Retrieval-Augmented Generation)

architecture. Nice-to-Haves

Exposure to Python for prototyping or basic data processing. Experience with event-driven architectures (Apache Kafka, RabbitMQ). Experience deploying applications on cloud platforms (AWS, GCP, or Azure). What we offer

Commitment to Professional Development Flexible and Collaborative Culture Total Rewards *Specific benefits are determined by employment type and location.

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