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AI Engineer

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1 Vacancy
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Job Location drjobs

Barcelona - Spain

Monthly Salary drjobs

Not Disclosed

drjobs

Salary Not Disclosed

Vacancy

1 Vacancy

Job Description

Our R&D department at Capitole continues growing and we are hiring an AI Engineer!

We are looking for someone who can help design and operate multi-agent LLM pipelines and other AI products. This includes workflows with LangGraph keep them observable and reliable in production deploy them in containerized cloud environments and providing robust long-term memory through vector databases and PostgreSQL. Good use of AI coding assistants like Cursor or Claude Code is a clear advantage and we expect you to move quickly inside large codebases with AI assistance.


Must-Have Skills

  • LangGraph expertise breaking complex QA tasks into sub-tasks
  • Experience with Prompt Engineering & LLM Ops familiar with LangSmith for tracing and metrics.
  • DevOps and Cloud experience working with Docker/Kubernetes CI/CD pipelines cloud platforms and infrastructure as code.
  • Worked with vector databases such as FAISS Pinecone Weaviate Milvus; applying the RAG pattern.
  • Know- how of memory engineering (buffers sliding windows vector storage)
  • Database Interaction PostgreSQL (Supabase a plus)

Nice-to-Have Skills

  • Web Scraping & Testing Frameworks Basic scraping with BeautifulSoup/Playwright/Selenium; familiarity with BDD (Cucumber/Gherkin) and Cypress for UI automation.
  • Basic Chatbot UI Rapid prototyping of a local chat interface in Streamlit.
  • CLI Development Building Python REPL tools with Typer.
  • Coding Assistants Confident daily use of Cursor or Claude Code.
  • Model Context Protocol (MCP) Awareness of the open-standard protocol that standardises how applications pass context to LLMs and tools enabling easier integrations.
  • Experience in research Published papers and a track record on R&D.


Whats next
This role starts with cutting-edge work on LLM agents and LangGraph pipelines but were building long-term AI capabilities with a heavy focus on innovation. Once this phase is complete well also explore classic ML/AI tasks including forecastring classification and explainable AI. A zest for research and innovation is key whether its prototyping new agents improving reliability or experimenting with model fine-tuning and emerging AI paradigms.

Employment Type

Full Time

Company Industry

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