AI Engineer – up to 80,000 + Benefits – Hybrid – London

Overview

In this role you will design, build and operate production-grade AI solutions within a high-performance tech function. You’ll work on end-to-end AI systems that span frontend, backend and data pipelines to deliver scalable, secure, business-driven AI capabilities. You collaborate with data scientists, engineers and stakeholders to turn enterprise requirements into robust AI delivery. This is a hands-on, full-stack role with a strong focus on Generative AI, Agentic AI and ML, offering meaningful impact across business processes and platforms.

Pay / Benefits

• Benefits

Responsibilities

• Design and maintain end-to-end AI solutions across UI, backend services and data pipelines
• Build, optimize and deploy AI/ML models for production readiness and scalability
• Deliver Generative AI, Agentic AI and traditional ML solutions aligned with enterprise needs
• Integrate AI systems with existing enterprise platforms for stability
• Collaborate with data scientists, engineers and business stakeholders to identify opportunities
• Provide technical guidance and mentorship to junior engineers
• Lead adoption of engineering standards across AI/ML delivery
• Stay updated with emerging AI tech and drive ongoing innovation

Key requirements

• Strong proficiency in Python with AI/ML/NLP libraries
• Hands-on experience with large language models (prompt engineering, fine-tuning, evaluation)
• Experience with Generative AI frameworks and agent-based AI frameworks
• Solid MLOps and LLMOps tooling and model lifecycle management
• Proven deployment experience on major cloud platforms with AI/ML services
• Strong software engineering foundations for scalable systems
• Experience delivering enterprise AI solutions including RAG-based architectures using vector databases
• Proven track record delivering full-stack AI/ML systems in enterprise environments
• Knowledge of advanced agent architectures and autonomous workflows
• Excellent communication and stakeholder management skills
• Experience supporting proposals, client-facing discussions or technical presentations

• communication
• stakeholder management
• mentorship
• Python
• NLP libraries
• LLMs and prompt engineering

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