AI Engineer (LLMs, Agents & Applied Data Science)

Overview

In this hands-on AI Engineer role, you’ll build and deploy AI and ML components for client projects, combining classic data science with GenAI and LLM-based features. You’ll operate under senior architects, delivering defined workstreams and turning designs into production-ready code. You’ll mentor junior colleagues, share learnings, and collaborate across client engagements to solve real problems. This is a delivery-focused position at the intersection of analytics and modern AI, offering breadth across technologies and client impact.

Pay / Benefits

• BDP Plus sabbatical program
• 25 days holiday + bank holidays
• 5 days holiday buy/sell option
• Private medical insurance
• Life cover
• Cycle to work scheme

Responsibilities

• Build, test, and deploy AI/ML components per designs by senior colleagues
• Develop GenAI/LLM-based features (prompting, retrieval-augmented generation, simple agent workflows)
• Deliver classical data science tasks (data prep, feature engineering, model training, evaluation)
• Translate designs into clean, production-ready code
• Contribute to model evaluation, testing, and monitoring
• Support and guide very junior resources and review their work
• Help peers unblock technical problems and share knowledge across the team
• Participate in client and team discussions and communicate work clearly

Key requirements

• Typically, 2–4 years’ experience in data science, ML, or AI engineering
• Solid grounding in core data science and ML
• Practical experience with LLMs and generative AI (prompting, RAG)
• Familiarity with AI agents and orchestration
• Strong Python and common data/ML libraries; good engineering habits
• Clear communicator and collaborative team player

• Clear communicator
• Collaborative team player
• Mentoring junior colleagues
• Python
• Data/ML libraries
• LLMs and generative AI

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