AI/LLM Engineer (Contract) - RAG Implementation | London (Mostly Remote) - Outside IR35 - Jan Start

Robson Bale Ltd; Greater London; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading AI solutions provider is seeking a skilled AI/LLM Engineer for a contract role focusing on RAG implementation in London. You will design and deploy AI solutions, working closely with product teams, while ensuring scalability and security. Candidates should have proven experience with RAG systems, strong ML Ops expertise, and a solid understanding of AWS infrastructure. This position allows for remote work and is expected to extend beyond three months.

Qualifications

• Proven experience developing and deploying RAG solutions in production.
• Strong background in LLM and agentic system development.
• Hands-on experience with ML Ops tools and workflows.

Responsibilities

• Design, build, and deploy RAG-based AI solutions.
• Collaborate with architects to ensure sound AI design and integration.
• Evaluate and compare AI solutions to identify optimal approaches.

Skills

Developing and deploying RAG solutions

ML Ops tools and workflows

Clear communication skills

Collaboration with teams

Tools

AWS

CI/CD

MCP

Job description

AI/LLM Engineer (Contract) - RAG Implementation | London (Mostly Remote) - Outside IR35 - Jan Start

We're seeking a skilled AI/LLM Engineer to help deliver Retrieval Augmented Generation (RAG) solutions for a major client project in London.

This is a hands‑on contract role suited to someone with strong implementation skills who can build reliable, production‑ready AI systems on AWS.

3 months initially — Will certainly extend

Market rate

The Role

You’ll play a key role in designing, building, and deploying advanced AI capabilities, working closely with technical and product teams. This position focuses on execution and delivery — developing scalable, secure solutions while contributing to best practices across the AI stack.

What You’ll Do

• Design, build, and deploy RAG-based AI solutions
• Develop agentic workflows and intelligent automation capabilities
• Collaborate with architects to ensure sound AI design and integration
• Build and maintain scalable ML applications on AWS
• Implement ML Ops pipelines for training, deployment, and monitoring
• Evaluate and compare AI solutions to identify optimal approaches
• Ensure security, compliance, and reliability of production systems
• Contribute to establishing good engineering practices for AI delivery

What You’ll Bring

• Proven experience developing and deploying RAG solutions in production
• Strong background in LLM and agentic system development
• Familiarity with MCP or similar model control frameworks
• Hands‑on experience with ML Ops tools and workflows (CI/CD, model life cycle, monitoring)
• Understanding of security and governance in AI systems
• Solid experience with AWS infrastructure and services
• Clear communication skills and ability to collaborate effectively with cross‑functional teams