Production AI Engineer: Build Scalable LLM Systems

Production AI Engineer: Build Scalable LLM Systems

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

At a Glance

  • Tasks: Build and ship production-grade AI systems, owning projects from idea to production.
  • Company: Radley James, a leader in innovative AI solutions.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Fast-paced environment with exciting challenges and career advancement.
  • Why this job: Join a high-caliber team and influence the future of AI production.
  • Qualifications: Experience with AI/LLM systems and familiarity with ML pipelines.

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

Radley James is seeking a hands-on Applied AI Engineer to build and ship production-grade AI systems. You will work across various elements including RAG pipelines and APIs, owning projects from idea to production.

The ideal candidate has experience with AI/LLM-powered systems, is familiar with ML pipelines, and thrives in fast-paced environments. This role offers a unique opportunity to influence AI production in a high-caliber team setting.

Production AI Engineer: Build Scalable LLM Systems employer: Radley James

Radley James is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the tech industry. With a focus on collaboration and employee growth, team members are encouraged to take ownership of their projects while working with cutting-edge technologies in a hybrid London setting. The company values creativity and offers unique opportunities for professional development, making it an ideal place for passionate individuals seeking meaningful and rewarding careers.

Radley James

Contact Details:

Radley James Recruitment Team

We think you need these skills to ace Production AI Engineer: Build Scalable LLM Systems

Applied AI Engineering
Production-grade AI Systems
RAG Pipelines
APIs
AI/LLM-powered Systems
ML Pipelines
Project Ownership