AI Engineer
Listed on 2026-09-20
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IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
This is an exciting opportunity to join a growing AI practice and work on cutting-edge projects spanning Generative AI, LLMs, AI Agents, Machine Learning, and Data Science. The role offers genuine responsibility, exposure to client-facing delivery, and a clear pathway to leadership.
Its hybrid working with your base office being Edinburgh, London, Manchester, Leeds or Birmingham.
The RoleAs an AI Engineer, you'll play a key role in delivering AI-powered solutions across a variety of client projects. You'll work with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and traditional machine learning techniques to solve real-world business challenges.
Working alongside senior AI and Data Science leaders, you'll own significant project work streams, turning solution designs into robust, production-ready software whilst helping to mentor junior colleagues and contribute to the growth of our AI practice.
What You'll Be Doing- Building, testing, and deploying AI and Machine Learning solutions
- Developing GenAI applications using LLMs, RAG architectures, and agentic workflows
- Delivering end-to-end data science activities including feature engineering, model training, and evaluation
- Writing clean, maintainable, production-focused Python code
- Supporting model evaluation, monitoring, and optimisation
- Collaborating with clients and project teams to deliver tangible business outcomes
- 2-4 years' experience in Data Science, Machine Learning, AI Engineering, or related fields
- Strong Python development skills and practical experience with common ML libraries
- Solid grounding in machine learning and data science fundamentals
- Hands-on experience with Generative AI, LLMs, Prompt Engineering, and RAG
- Understanding of AI Agent frameworks and orchestration approaches
- Excellent communication and stakeholder engagement skills
- Collaborative mindset with a passion for learning and innovation
- Experience with Azure AI services and cloud-based AI platforms
- Exposure to MLOps and LLMOps practices
- Previous mentoring or coaching experience
- Consulting or client-facing delivery experience
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