Referment
Lead AI Engineer (F8F5719)
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
About the Role
Referment is working with a fast-growing UK wealth infrastructure company whose digital investment system is transforming how financial advisers and their clients invest. As the business scales, it is growing a multi-disciplinary Data, Analytics and AI function to unlock the full potential of its data assets — and it is looking for a Lead AI Engineer to shape that capability from the ground up.
This is a high-impact, hands-on leadership role. Reporting to the Head of Data and Analytics, you will lead the design, build and productionisation of the company's AI systems and infrastructure on Google Cloud, driving business growth and operational efficiency. You'll also recruit and mentor a multidisciplinary team of analysts, data scientists and data engineers, embedding AI into both products and internal operations.
The Role
You'll set the technical vision and roadmap for the company's AI capabilities, building on its data foundations in GCP and ensuring alignment with business goals. That means evaluating and selecting the tools, frameworks and cloud services needed to build scalable, reliable AI products — and ensuring AI systems adhere to applicable data regulatory requirements, AI ethical guidelines and explainable AI techniques.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
You'll work with the wider business to explore challenges and opportunities for both internal and external users, assessing potential impacts so the team focuses on projects that maximise their contribution. You'll leverage a diverse range of internal multi-modal data — time-series data, documents, emails and phone calls — to develop AI systems that enhance the quality and efficiency of internal operations.
On the operations side, you'll ensure robust model governance through a comprehensive model registry with version control and deployment standards, define success metrics and implement production model monitoring (including prediction latency and performance decay), design end-to-end MLOps pipelines, provision data components through Infrastructure as Code, and monitor, analyse and optimise the cost efficiency of the AI estate.
You'll also build the AI engineering capability — recruiting AI engineers, providing technical guidance, mentorship and code reviews — and work closely with product and engineering teams to translate requirements into technical specifications and oversee delivery from conception to production.
What We're Looking For
- 7+ years' proven experience in data-driven systems or AI engineering
- Experience architecting AI systems using LLMs, RAG and AI agents, and 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 experience with Docker, and Infrastructure as Code such as Terraform
- A Bachelor's or Master's degree in Computer Science, Engineering or a related field
- Excellent written and verbal communication and interpersonal skills
Get help with your application
Your very own career expert that helps elevate your application to the next level.
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 based in London with hybrid working, three days a week in the central London office.
This Could Suit
A senior AI/ML engineer who has already taken LLM, RAG or agentic systems into production and now wants to own the entire AI capability of a business — architecture, MLOps, governance, cost and people leadership — in a data-rich, product-led fintech environment.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location