AI Engineer

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 Role

As 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 workstreams, 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

What We're Looking For

• 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 experienceConsulting or client-facing delivery experience