AI Engineer

Referment is working with a fast-growing UK wealth infrastructure company whose digital investment system is transforming how financial advisers and their clients invest. Its strategy has always centred on reducing friction in advisers' administrative work, and AI is opening the next level of automation and simplification — so the business is growing its multidisciplinary Data, Analytics and AI function. This is a high-impact, hands-on role with the opportunity to shape the company's AI capabilities from the ground up. Reporting to the Head of Data and Analytics, you'll join a team of experienced AI engineers building innovative solutions that make life easier for advisers and internal teams alike. At the heart of the role is the design and delivery of AI-powered systems that streamline administrative tasks, automate communications and uncover smarter ways to support clients — a genuine opportunity to help transform the day-to-day operations of the wealth advisory industry at scale. The Role You'll work with the wider business to explore challenges and opportunities for both internal and external users, assessing potential impacts so effort goes where it makes the biggest difference. You'll build robust AI solutions that reduce administrative effort and free up more client time, and you'll leverage a diverse range of internal multi-modal data — time-series data, documents, emails and phone calls — to develop systems that enhance the quality and efficiency of internal operations. You'll also own the discipline behind the systems: maintaining a comprehensive model registry with version control and deployment standards across production models, defining success metrics, and implementing advanced production model monitoring that tracks metrics like prediction latency and model performance decay. You'll design and build end-to-end MLOps pipelines to drive continuous improvement in AI system performance. Collaboration matters here too. You'll work closely with colleagues in the AI team to build reusable components that allow AI tooling to scale, translate requirements into technical specifications and project plans, and help technical and non-technical colleagues across the business leverage AI capabilities in an optimal and secure way. What We're Looking For

• 5+ years' proven experience in data-driven systems or AI engineering
• Experience building AI systems using LLMs, RAG and AI agents
• Experience turning AI/ML prototypes into robust production systems
• Experience with AI/MLOps pipelines and production monitoring systems
• Advanced proficiency in Python and SQL, and preferably other languages
• Containerisation technologies including Docker, and Infrastructure as Code such as Terraform
• Excellent written and verbal communication, presentation and interpersonal skills
• A Bachelor's or Master's degree in Computer Science, Engineering or a related field Also Valuable
• Startup or high-growth environment experience
• Knowledge of data privacy and AI regulation, preferably in financial services
• Experience building infrastructure and tooling for A/B testing and experimentation
• GCP Vertex AI experience (Pipelines, Model Registry, Endpoints)
• GCP Professional Machine Learning Engineer certification This is a permanent role on a hybrid basis, with three days a week in the central London office. The company is unable to offer visa sponsorship for this position. This Could Suit A hands-on AI engineer who has taken LLM, RAG or agentic solutions beyond prototypes and into production — someone who enjoys both building the systems and the MLOps rigour behind them, and who wants their work to visibly reduce administrative burden in a data-rich fintech setting.