Job Description

Fundment is a fast-growing wealth infrastructure company, building on our cuttin edge digital investment system to transform the £3 trillion UK wealth management market. We are passionate about revolutionising the investment experience for financial advisers and their clients by combining our innovative proprietary technology with exceptional customer service. As we scale, we are growing our multi-disciplinary Data, Analytics & AI function to unlock the full potential of our data assets.

About the Role

This is a high-impact hands-on leadership role with the opportunity to shape Fundment’s AI capabilities from the ground up. Reporting to our Head of Data& Analytics, you will lead the design and delivery of AI systems and infrastructure to drive business growth and enhance operational efficiency. Key Responsibilities

AI Architecture & Strategy:

• Set the technical vision and roadmap for Fundment’s AI capabilities, building on our data foundations in GCP and ensuring alignment with our business goals.

• Evaluate and select optimal tools, frameworks and cloud services to allow us to build scalable and reliable AI products.

• Ensure our AI systems adhere to all applicable data regulatory requirements, AI ethical guidelines, and employ Explainable AI (XAI) techniques

AI Product Development:

• Work with the wider business to explore challenges and opportunities to both internal and external users. Assess potential impacts to ensure we focus on projects that maximise our contribution to the business.

• Build industry leading, innovative and robust AI solutions that delight our customers and drive business growth.

• Leverage our diverse range of internal multi-modal data (including time-series data, documents, emails and phone calls) to develop AI systems to enhance the quality and efficiency of our internal operations.
  

AI/ML Operations:

• Ensure robust model governance by maintaining a comprehensive model registry with version control and deployment standards across all production models

• Define success metrics for AI solutions and implement advanced production model monitoring, tracking key metrics like prediction latency and model performance decay.

• Design and build end-to-end MLOps pipelines to drive continuous improvement in AI system performance

• Ensure that all data components are provisioned and controlled through Infrastructure As Code (IaC)

• Monitor, analyze, and optimise the cost efficiency of our AI systems
  

Team Leadership & Mentorship:

• Build our AI engineering capability and recruit other AI engineers of the highest calibre

• Provide technical guidance, mentorship, and code reviews to our multi disciplinary team of analysts, data scientists and data engineers.

• Work closely with our product and engineering teams to embed our AI capabilities into our platform.

• Translate requirements into technical specifications and project plans, overseeing execution from conception to production.

• Collaborate with cross-functional teams across the company to help both technical and non-technical users leverage our AI capabilities in an optimal and secure way.
  

Required Skills/Experience

• Experience: Proven experience (7+ years) in data-driven systems or AI engineering

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

• Core Technical skills:

1. Advanced proficiency in SQL for data manipulation and analysis

2. Advanced proficiency in Python and preferably other programming languages

3. Experience with containerization technologies including Docker.

4. Experienced with Infrastructure as Code (e.g. Terraform)

• AI Experience:

1. Experienced in architecting AI systems using LLMs, RAG and AI agents.

2. Experienced in turning AL/ML prototypes into robust production systems

3. Experience with AI/MLOps pipeline and production monitoring systems

• Communication: Excellent written and verbal communication, presentation and interpersonal skills
  

Preferred Skills/Experience

• Experience in a startup or high-growth environment.

• Knowledge of data privacy and AI regulation, preferably within financial services

• Experience in building the infrastructure and tools to support effective A/B testing and experimentation.

• Experience in GCP Vertex AI platform, including Vertex AI Pipelines, Model Registry, and Vertex AI Endpoints.

• GCP Professional Machine Learning Engineer certifications.
  

Pay range and compensation package

Competitive salary. 28 days annual leave plus bank holidays, enhanced pension contribution, enhanced parental leave, private healthcare, regular salary reviews, hybrid working 3 days a week in our beautiful Fitzrovia based offices. Why join us?

Become part of our flexible, dynamic and supportive work environment, where our innovative team values your ideas and collaboration drives our success together.

Make an impact from day one and challenge yourself to continually improve, raise standards and see how your work can contribute to future goals.

We are happy to consider any reasonable adjustments that applicants may need during the recruitment process.

• Be part of a modern, inclusive, high-trust engineering culture

• Take ownership and ship code that directly improves client outcomes

• Work with a smart, friendly team that values balance, growth, and support

• Pension 6% employer contribution, minimum 2% employee contribution.

• BUPA Private Health Insurance – fully paid for by the company, for you and your immediate family.

• Medicash Cashplan – fully paid for by the company, for you and your immediate family.

• Travel insurance – fully paid for by the company, for you and your immediate family.

• Life Assurance – 4 x base salary.

• Employee Assistance Programme

• 28 days annual leave plus bank holidays.

• Paid compassionate leave – up to 5 days per year.

• Enhanced paternity/maternity/adoption leave – 16 weeks at full pay after 12 months of service.

• Jury service – 10 days at full pay.

• Hybrid working arrangements – 3 days per week in the Fitzrovia office.

• Coaching&Counselling sessions

• Training Budget

• Annual pay review

• Annual training budget