Entry: AI Engineer

Entry: AI Engineer

Who we are

Artefact brings a new generation of consulting, leveraging consumer data to drive higher impact decisions and strategies. It has never been as hard for key stakeholders in global organisations to drive their business, and the need for data to inform the best way forward is key.

That’s why, at Artefact, we are putting together a unique set of talents: consultants, data scientists, ML engineers, digital specialists, and data analysts.

We have 1 800 employees across 2 3 offices globally, and are focused on accelerating digital transformation, working for highly prestigious international clients that make us proud of our work and that also recognise, we believe, the added value of years of research in AI across multiple strategic and operational challenges that they face.

What you will be doing

Engineering the Next Generation of Intelligence

We are seeking an Entry level AI Engineer who is ready to move beyond "GPT wrappers" and build production-grade AI services. This is a role for a high-potential engineer with a strong foundation in Python and a relentless curiosity about the generative AI landscape. You will support the team in building, testing, and deploying LLM-powered features, ensuring our AI outputs are reliable, structured, and scalable.

Key Responsibilities

• Design and refine dynamic prompt templates using conditional logic to improve response quality and reasoning.
• Help build and maintain multi-agent workflows in Python, using frameworks like LangChain , AutoGen , CrewAI or similar.
• Develop and maintain entry-level ETL/ELT pipelines to move data into vector stores and data lakes for RAG systems.
• Execute "LLM -as-a-judge" testing frameworks to score model outputs and identify instances of hallucination or logic errors.
• Work closely with the engineering team to integrate AI microservices into our core application stack.

Your Toolkit

• Professional experience or a strong portfolio in Python and standard software/backend engineering practices (Git, unit testing).
• Familiarity with LLM APIs, prompt design, and retrieval-augmented generation (RAG) concepts.
• Exposure to cloud platforms (preferably Azure) and containerization tools like Docker
• A Bachelor’s/Honours degree in Computer Science or a related technical field.