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# AI Engineer

- **Company:** Harnham
- **Location:** Greater London, UK
- **Experience:** Experienced
- **Salary:** £75,000.0 - £85,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Applications Architecture, Microsoft Azure, Continuous Integration, Python (Programming Language), Machine Learning, Software Engineering, Large Language Models, Model Validation, Generative AI, Containerization, Machine Learning Operations, Virtual Agents, Databricks
- **Published:** August 12, 2026
- **Apply:** https://www.reed.co.uk/jobs/ai-engineer/57222124

## About the Role

* Strong Python and software engineering background
 * Commercial experience delivering machine learning models into production
 * Hands-on experience with GenAI, LLMs and AI application development
 * Knowledge of MLOps, LLMOps, CI/CD and containerisation
 * Experience with cloud platforms, ideally Azure
 * Understanding of model evaluation, monitoring and responsible AI
 * Strong communication skills with the ability to translate business requirements into technical solutions

Skills

 * AzureML
 * LLMs
 * Databricks
 * Python

## Description

London (Hybrid, 3 days per week)
This is an opportunity to join a newly formed AI function at a pivotal stage of growth. You'll work on high-impact AI initiatives across machine learning, Generative AI and Agentic AI, helping to shape how AI is adopted and scaled across a major organisation.
The Company
Our client is investing significantly in AI as part of a large-scale transformation programme. Operating through a central AI Centre of Excellence, they are building scalable, production-ready AI solutions that deliver measurable business value. This is a chance to join early, influence standards and best practice, and play a key role in a growing AI engineering team.
The Role
You will:

 * Design, build and deploy AI and machine learning solutions from concept to production
 * Develop applications using LLMs, Generative AI and Agentic AI frameworks
 * Deliver predictive, optimisation and automation use cases
 * Build robust MLOps and LLMOps processes, including monitoring and evaluation
 * Work closely with engineers, data scientists, product teams and business stakeholders
 * Help establish AI engineering standards, governance and responsible AI practices
 * Contribute to the long-term technical direction of the AI team


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