AI Engineer

Change Digital – Digital & Tech Recruitment

City of Edinburgh

Hybrid

GBP 45,000 - 75,000

Full time

15 hours ago
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Job summary

Change Digital – Digital & Tech Recruitment seeks an AI Engineer to deliver AI-powered solutions across client projects, leveraging LLMs, RAG, AI Agents, and traditional ML techniques to tackle real-world business challenges.

You will work with senior AI and data science leaders, own major workstreams, and turn solution designs into production-ready software while mentoring junior colleagues and helping grow our AI practice.

Qualifications

  • 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

Responsibilities

  • 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

Skills

Python development
ML libraries
AI fundamentals
Generative AI
LLMs
RAG
Prompt engineering
Azure AI services
MLOps
Mentoring
Client-facing delivery

Job description

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 experience
  • Consulting or client-facing delivery experience
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