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# Engineer - AI SDLC Enablement (All Genders)

- **Company:** Cerrará Pronto
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Systems Engineering, Automation of Tests, Code Generation, Computer Programming, Continuous Integration, Python (Programming Language), Systems Development Life Cycle, Software Engineering, Large Language Models, Kotlin, Kubernetes, Terraform, Docker
- **Published:** July 20, 2026
- **Apply:** https://www.adzuna.es/contact-us.html

## About the Role

+ Tech-agnostic mindset with strong programming experience in one or more of the following languages: Java, Python, JavaScript, or Kotlin, or broad working knowledge across multiple of these languages.
 + 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.
Core Competencies

 + MCP Engineering - building modular, context-aware AI tooling
 + Context Engineering - structuring inputs for reliable AI reasoning
 + AI-Augmented Architecture - integrating AI into engineering systems
 + Product Thinking - identifying high-value GenAI use cases

## Description

With over 25 years' experience, plus the same enormous passion and ambition we had on day-one, we're trailblazers in the pet e-commerce industry. Our solutions make over 12 million customers genuinely happier - and that's something we really care about. We work together to continually adapt; embracing change and the challenges it brings so that we can keep doing better. Join us and discover a place where your potential meets your passion for pets. That's the power of plus., The Senior AI Engineer is responsible for embedding AI capabilities across the software development lifecycle (SDLC) to improve engineering productivity, delivery quality, and automation. The role focuses on building intelligent developer workflows using Model Context Protocol (MCP), context engineering, LLM orchestration, and AI-driven tooling.
Key Responsibilities

 + 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.


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