Senior AI Engineer — AI-Driven Developer Tools Architect

zooplus; Madrid; Híbrido; EUR 70.000 - 110.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid working

20% discount on products

Wellbeing offers

Subsidised transport or bike leasing

20 days abroad in approved countries

Descripción de la vacante

zooplus is seeking a Senior AI Engineer to embed AI capabilities across the SDLC, focusing on MCP context engineering and LLM orchestration to boost engineering productivity. The role drives AI tooling and automated testing within Acquisition & Retention, collaborating across engineering, platform, and product teams.

The ideal candidate has hands-on experience with LLMs in engineering workflows, a tech-agnostic mindset, and deep knowledge of Docker/Kubernetes/Terraform, as well as RAG and

Formación

• Tech-agnostic mindset with strong programming experience in one or more of Java, Python, JavaScript, or Kotlin.
• Hands-on experience integrating LLMs into engineering or product workflows.
• Good understanding of RAG, embeddings, and vector databases.
• Experience with Docker, Kubernetes, and Terraform.
• Experience with intelligent test automation and CI/CD pipelines.

Responsabilidades

• Design and implement AI-driven SDLC accelerators such as code generation, review automation, smart testing, and documentation support.
• Develop MCP-based extensions and context-aware tools to streamline developer workflows.
• Apply context engineering to improve LLM reasoning, accuracy, and relevance across engineering use cases.
• Build LLM-integrated CI/CD workflows for pull request analysis, test automation, and deployment support.
• Collaborate with engineering, platform, and product teams to identify and scale AI adoption opportunities.

Conocimientos

LLM integration

CI/CD automation

Context engineering

AI tooling

Herramientas

Docker

Kubernetes

Terraform

Vector databases

Descripción del empleo

zooplus is seeking a Senior AI Engineer to embed AI capabilities across the SDLC, focusing on MCP context engineering and LLM orchestration to boost engineering productivity. The role drives AI tooling and automated testing within Acquisition & Retention, collaborating across engineering, platform, and product teams.

The ideal candidate has hands-on experience with LLMs in engineering workflows, a tech-agnostic mindset, and deep knowledge of Docker/Kubernetes/Terraform, as well as RAG and