AI Architect – up to 100,000 + Benefits – Hybrid – London

Overview

In this senior, hybrid London-based role you will lead end-to-end AI solutions across enterprise environments, blending strategic advisory with hands-on delivery. You drive Generative and Agentic AI architectures, guiding stakeholders and shaping scalable, production-grade platforms. You partner with business and delivery teams to convert requirements into robust data and AI architectures and oversee multi-disciplinary implementations. The role offers impact at scale, influencing transformation and cost optimisation through intelligent automation. You will produce thought leadership and stay ahead of emerging AI trends to fuel competitive advantage.

Responsibilities

• Qualification of opportunities with commercial and delivery teams and shaping proposals
• Act as trusted advisor in discovery sessions, workshops and bid processes
• Translate business requirements into enterprise-grade Data and AI architectures
• Design and architect Generative AI and Agentic AI solutions for operations and workflows
• Lead complex AI implementations delivering measurable value
• Evaluate models, frameworks, orchestration tools and platforms
• Architect and scale LLM-powered applications including chatbots and agent-based systems
• Produce thought leadership content and contribute to go-to-market propositions
• Maintain awareness of emerging technologies and the competitive AI landscape
• Collaborate with data science, engineering and business teams to design end-to-end solutions
• Contribute to account strategy aligning technical delivery with business priorities
• Drive productivity and cost optimisation through intelligent automation

Key requirements

• Proven experience architecting Generative AI, Agentic AI, ML and automation solutions
• Strong prompt engineering, RAG pipelines, model tuning, MLOps and LLMOps
• Enterprise-scale RAG solutions with LLMs and vector databases
• Design AI platforms integrating with existing enterprise tech stacks
• Hands-on experience with core GenAI frameworks and agent-based AI concepts
• Deployment on at least one major cloud platform with AI/ML services
• Solid software engineering foundation for scalable AI systems
• Advanced Python with AI/ML frameworks
• Experience with MLOps and LLMOps tooling including containers and orchestration
• Delivering applications using state-of-the-art LLMs with prompt design and evaluation
• Understanding of advanced agent architectures, reasoning systems and eval methodologies
• Excellent stakeholder engagement and consulting capability
• Experience leading and mentoring AI or software engineering teams

• stakeholder engagement
• consulting capability
• leadership
• Generative AI
• Agentic AI
• prompt engineering

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