Artificial Intelligence Engineer

Artificial Intelligence Engineer | 6 Month Contract (OIR35) | London

We're working with a forward-thinking organisation that is investing heavily in Generative AI, LLMs and agentic AI systems. They are looking for an experienced AI Engineer to design, build and deploy production-grade AI solutions that sit at the heart of real business workflows.

This is a hands-on contract role suited to someone who has delivered RAG pipelines, multi-agent systems and NLP-driven applications in live environments, ideally within complex or regulated domains.

Location: London (2 days onsite)

Contract: 6 Months (OIR35)

Rate: £400-500 p/day

Key Skills:

• Strong commercial experience as an AI Engineer / ML Engineer / Applied AI Scientist

• Advanced Python experience for ML and AI development

• Hands-on experience with LLMs & Generative AI, including:

• Retrieval-Augmented Generation (RAG)

• Prompt & context engineering

• Agentic / multi-agent architectures

• Experience with frameworks such as LangChain, LangGraph, LangSmith or similar

• Solid NLP background (tokenisation, embeddings, transformers, BERT-style models, sentiment analysis)

• Experience integrating vector databases (e.g. Azure AI Search, OpenSearch, Pinecone, Weaviate)

• Cloud experience on Azure, AWS or GCP

• Familiarity with MLflow, model evaluation frameworks, observability & monitoring

• Strong understanding of deploying AI systems into real-world production environments

Key Responsibilities:

• Design and build Generative AI solutions using LLMs, RAG architectures and agent-based workflows
• Develop and orchestrate multi-agent AI systems (e.g. supervisor and specialist agents)
• Implement retrieval pipelines using vector databases to ground LLM responses
• Build and optimise NLP pipelines for sentiment analysis, intent detection and document understanding
• Deploy AI/ML models into production using cloud-native architectures
• Implement MLOps best practices including CI/CD, monitoring, observability and evaluation
• Work closely with engineering, product and data teams to translate business problems into AI solutions
• Ensure solutions are scalable, interpretable and production-ready

If this sounds like you, !

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