AI Engineer (LLMs, Agents & Applied Data Science)

As our AI practice grows, we are looking for a capable, hands-on AI Engineer to help build and deliver the solutions at the heart of our client work. Coming from a data science background, you are equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). You enjoy building, you write dependable code, and you turn well-defined designs into working software.

This is a delivery-focused role that sits a level below our Lead Data Scientists. You will own meaningful workstreams within a project rather than the whole engagement, working to an architecture and plan shaped by more senior colleagues. In return, you will gain breadth across modern AI, exposure to real client problems,

You will also be a supportive presence within the team, helping your peers solve problems, sharing what you learn, and giving day-to-day guidance to graduate and junior resources working alongside you.

Required skills & experience:

• Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.
• Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.
• Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them.
• Translate solution designs into clean, well-documented, production-minded code.
• Contribute to model evaluation, testing, and monitoring.
• Support and guide very junior and graduate resources, reviewing their work and helping them grow.
• Help peers unblock technical problems and share knowledge across the team.
• Take part in client and team discussions and communicate your work clearly.

To qualify for this role, you must have:

• Typically, 2–4 years' experience in data science, machine learning, or AI engineering.
• Solid grounding in core data science and machine learning.
• Practical experience with LLMs and generative AI, including prompting and RAG.
• Familiarity with how AI agents are built and orchestrated.
• Strong Python and common data/ML libraries; good engineering habits.
• Clear communicator and collaborative team player.

Ideally, you’ll also have, but not essential:

• Exposure to cloud AI platforms, Azure a plus.
• Experience practicing MLOps and LLMOps.
• Early experience mentoring junior colleagues.
• Interest in consulting and client-facing delivery.

You must be: