Recruiting for a hands-on AI Engineer to join a team focused on embedding AI into the way the business operates

You'll work across AI engineering, process redesign, solution architecture and change delivery, picking up problems early and staying with them until they're live and delivering value.

Day to day, you'll partner with people across the business, tech, data and risk/control teams to understand how things currently get done, spot where AI genuinely helps, and then build something that's safe, reliable and actually gets adopted. 

Responsibilities

• Work alongside business teams to spot opportunities where AI can lift how processes and customer experiences run
• Build AI-powered apps, autonomous agents, smart workflows and retrieval-based (RAG) tools
• Handle orchestration, context management, APIs, data and integration work needed to get things into production
• Move fast on prototypes, test them against reality, and refine based on what you learn
• Make and defend technical design calls, and help set the standard for how AI gets adopted elsewhere in the business
• Build out testing, evaluation and monitoring approaches, guardrails, regression checks, observability 
• Weigh up model behaviour, edge cases and failure risks, balancing quality against speed, cost and user experience
• Get comfortable in structured and unstructured data, SQL, APIs, cloud infra, CI/CD pipelines, logging and live support
• Take solutions from prototype to something the business can actually rely on
• Share knowledge and lift AI capability across both business and technical teams
• Track and report back on the real-world impact and uptake of what you build

Experience

Ideally you'll have:

• 5+ years driving technology-led change, with real experience building AI-powered solutions
• Practical know-how in AI system design and common application patterns
• Runs on the board shipping AI apps, agents, automated workflows or RAG-based tools
• Solid grasp of agent orchestration, context engineering and integration approaches for AI systems
• Hands-on experience with Python and/or TypeScript
• Confidence working across APIs, SQL, data pipelines, cloud platforms, integrations, CI/CD and production support
• Experience setting up evaluation methods, test harnesses, regression checks, guardrails and monitoring for AI systems
• A working understanding of how models behave, where they fail, and how to judge them once they're live
• A quick-learning mindset, comfortable picking up new tools and frameworks rather than sticking to one platform
• Background in any mix of AI engineering, software development, data, automation, solution architecture or business analysis