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AI

AI Engineer

Job Details

Work Mode

Remote

Experience

Mid

Employment

Full-time

Salary

£80,000 - £85,000 p/y

Posted Today

Tech Stack

Required technologies & tools

Python Kubernetes Git Docker CI/CD PyTorch Nlp Llms Pydantic Azure Databricks Langchain Mlflow Rag Azure Machine Learning Azure Ai Foundry Embeddings Langgraph Vector Search

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Perks & Benefits

Hybrid work arrangement

About the Role

AI Engineer (LLMs / Azure / MLOps)
Global Professional Services Firm
Location: London
Working: Hybrid (3 days office / 2 days remote)
Salary: Up to £85k + benefits

The Role
An exciting opportunity to join a global professional services organisation investing heavily in AI, with a focus on delivering enterprise-grade AI products that solve complex, document-centric business challenges.

You will design, build and deploy production-ready AI solutions across the Microsoft Azure ecosystem. This is a hands-on engineering role focused on taking LLM-powered applications from experimentation into scalable, secure and reliable production environments.

We're particularly interested in engineers who have built AI solutions around document intelligence, enterprise search, knowledge management, NLP or Retrieval-Augmented Generation (RAG), rather than purely research-focused AI.

Key Responsibilities

  • Design, build and deploy production-ready LLM and Machine Learning solutions using Azure Databricks, Azure Machine Learning and Azure AI Foundry
  • Develop scalable AI applications using modern orchestration frameworks including LangChain and LangGraph
  • Build agentic AI workflows and enterprise AI services using retrieval, tool-calling and orchestration patterns
  • Deliver end-to-end AI/ML pipelines covering experimentation, deployment, monitoring and optimisation
  • Apply MLOps and LLMOps best practices across model lifecycle management, governance and production monitoring
  • Work closely with Data Engineers, Platform Engineers and business stakeholders to deliver enterprise AI solutions
  • Contribute to AI products across document intelligence, knowledge search, workflow automation and AI assistants
  • Help shape engineering standards, Responsible AI practices and cloud governance across the AI platform


Key Requirements

  • Commercial experience building and deploying LLM-powered applications into production
  • Strong hands-on experience with Azure Databricks, Azure Machine Learning and ideally Azure AI Foundry
  • Good understanding of MLOps and LLMOps
  • Excellent Python engineering skills with experience using frameworks such as LangChain, LangGraph, PyTorch and Pydantic
  • Experience with RAG, vector search, embeddings, prompt engineering and enterprise retrieval architectures
  • Experience building AI solutions within document-heavy environments such as legal, financial services, insurance or similar enterprise organisations would be highly advantageous
  • Experience with Docker, Kubernetes, MLflow, CI/CD and Git-based development
  • Strong communication skills with the ability to work across technical and non-technical teams


This is an excellent opportunity to join a business at the start of an exciting AI transformation, working on real-world AI products that are already delivering value across the organisation.

No sponsorship available.

Get in touch for more details -


McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.

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