RAG & AI Data Engineer: Build Scalable AI Pipelines

RAG & AI Data Engineer: Build Scalable AI Pipelines

Full-Time 80000 - 100000 Β£ / year (est.) No working from home possible
Diagonal recruitment

At a Glance

  • Tasks: Design and build data pipelines for cutting-edge AI applications.
  • Company: Diagonal recruitment, a leader in innovative tech solutions.
  • Benefits: Competitive salary, flexible working hours, and opportunities for skill development.
  • Other info: Exciting role with potential for career advancement in a dynamic environment.
  • Why this job: Join us to shape the future of AI with impactful projects.
  • Qualifications: Strong understanding of data architecture and experience with diverse datasets.

The predicted salary is between 80000 - 100000 Β£ per year.

Diagonal recruitment is looking for a skilled candidate to design and build data pipelines to support AI applications. You will develop Retrieval-Augmented Generation (RAG) architectures and create vector databases to enhance data retrieval and performance.

The ideal candidate has a strong understanding of data architecture and experience with structured and unstructured datasets. This role focuses on practical AI implementation, ensuring reliable foundations for AI systems in the United Kingdom.

RAG & AI Data Engineer: Build Scalable AI Pipelines employer: Diagonal recruitment

Diagonal recruitment is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation within the AdTech sector. With a focus on employee growth, you will benefit from hybrid working flexibility, comprehensive health plans, and generous holiday allowances, making it an ideal place for those seeking meaningful and rewarding employment in London.

Diagonal recruitment

Contact Details:

Diagonal recruitment Recruitment Team

We think you need these skills to ace RAG & AI Data Engineer: Build Scalable AI Pipelines

SQL
Python
Data Pipeline Development
Problem-Solving Skills
Data Engineering
API Integration
Communication Skills